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IGE: Track 1: Empowering Tomorrow's Scholars: A Comprehensive Training Initiative for Graduate Students in Scientific Peer Review
|
NSF
|
10/01/2024
|
09/30/2026
| 499,992 | 499,992 |
{'Value': 'Standard Grant'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Karen McNeal', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922138'}
|
This National Science Foundation Innovations in Graduate Education (IGE) award facilitates the development and implementation of a comprehensive graduate curriculum designed to enhance scientific literacy, peer review skills, and communication capabilities among STEM graduate students. Recognizing these skills' critical role in advancing scientific knowledge and career progress, this program seeks to equip graduate students with the tools necessary to critically evaluate scientific literature and contribute meaningfully to the peer review process. This innovative curriculum will foster a community of skilled reviewers and effective communicators, accelerating the dissemination of accurate scientific knowledge and improving the quality of scientific research.<br/><br/>The program will immerse graduate students in peer review and publishing processes through hands-on experiences. This includes navigating preprint platforms, evaluating cutting-edge scientific literature with high impact, and participating in peer review processes with the editorial board of a preprint overlay journal. The program aims to equip graduate students to rapidly evaluate preprint articles, providing scientific credibility to unreviewed articles with high societal impacts while combating scientific misinformation. The pilot program will consist of two cohorts of graduate students to initially develop a curriculum based on broadly applicable open-access online educational materials, including audio and video recordings, written content, and interactive workshops. This curriculum will be evaluated for its effectiveness in enhancing graduate student outcomes such as scientific literacy, comprehension, confidence in peer review processes, and community involvement. The educational model and online training materials will also be assessed for accessibility and scalability to expand and disseminate the peer review training program and materials to low- and middle-income countries and communities. Increased access to these materials aims to address equity and social justice issues in science dissemination and participation, representing a strategic investment in global scientific capacity-building, collaboration, and sustainable development.<br/><br/>The Innovations in Graduate Education (IGE) program is focused on research in graduate education. The goals of IGE are to pilot, test and validate innovative approaches to graduate education and to generate the knowledge required to move these approaches into the broader community.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/05/2024
|
08/05/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2429533
|
[{'FirstName': 'Sarah', 'LastName': 'Klass', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Sarah Klass', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A054Q', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'STEFANO', 'LastName': 'BERTOZZI', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'STEFANO M BERTOZZI', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A054H', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'University of California-Berkeley', 'CityName': 'BERKELEY', 'ZipCode': '947101749', 'PhoneNumber': '5106433891', 'StreetAddress': '1608 4TH ST STE 201', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'CA12', 'ORG_UEI_NUM': 'GS3YEVSS12N6', 'ORG_LGL_BUS_NAME': 'REGENTS OF THE UNIVERSITY OF CALIFORNIA, THE', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of California-Berkeley', 'CityName': 'BERKELEY', 'StateCode': 'CA', 'ZipCode': '947101749', 'StreetAddress': '1608 4TH ST STE 201', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'CA12'}
|
{'Code': '260Y00', 'Text': 'Innovations in Grad Education'}
|
2024~499992
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2429533.xml'}
|
GOALI: Segregation and Mixing of Cohesive Particles
|
NSF
|
09/01/2024
|
08/31/2027
| 448,916 | 448,916 |
{'Value': 'Standard Grant'}
|
{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}
|
{'SignBlockName': 'Shahab Shojaei-Zadeh', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928045'}
|
A major challenge in processing granular materials such as grains, pellets, beads, and powders in chemical, consumer product, and pharmaceutical manufacturing is that cohesive forces between particles affect their flow and mixing. The impact can be profound — poor mixing of active ingredients with fillers in the pharmaceutical industry can result in pills with too much active ingredient, risking overdose for the patient, or too little active ingredient to have the intended medical impact. The problem is that as granular materials flow, particles of different sizes tend to de-mix, or “segregate.” Although models to predict segregation and mixing are available for non-cohesive particles, the segregation behavior changes dramatically for “sticky” particles, which are very common in industry. The issue is further complicated because particle cohesion can be advantageous in some situations and problematic in others — the “stickiness” of cohesive particles can prevent unwanted segregation but also can reduce the flowability of powders or clog production equipment. This research will transform the understanding of the segregation and mixing of cohesive particles which will lead to physics-based models that can be used to design manufacturing processes that prevent segregation and promote mixing of cohesive granular materials in diverse areas ranging from pharmaceutical production to additive manufacturing.<br/><br/>When granular materials flow, small particles tend to fall between larger ones such that particles of different sizes de-mix, or “segregate.” Physics-based models for segregation developed over the past decade work well for non-cohesive particles but do not apply to cohesive particles. The goals of this research are to gain a fundamental understanding of how cohesive particles segregate due to differences in size and to develop predictive approaches that can be used to ensure that particles remain mixed. Computer simulations and experiments will be used to characterize the segregation of flowing cohesive particle mixtures to determine the dependence of segregation on flow and particle parameters as well as to examine the underlying physics of cohesive particle segregation at the particle scale. The resulting understanding of mechanisms at both particle and flow levels will lead to a continuum model for segregation of cohesive particles analogous to that for segregation of non-cohesive particles. Not only will this research transform the understanding of segregation and mixing of cohesive particles, but it will also result in a transition from current ad hoc approaches for predicting cohesive particle segregation and mixing to physics-based models.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/15/2024
|
08/15/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2429545
|
[{'FirstName': 'Paul', 'LastName': 'Umbanhowar', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Paul Umbanhowar', 'EmailAddress': '[email protected]', 'NSF_ID': '000413820', 'StartDate': '08/15/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Richard', 'LastName': 'Lueptow', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Richard M Lueptow', 'EmailAddress': '[email protected]', 'NSF_ID': '000334479', 'StartDate': '08/15/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Yi', 'LastName': 'Fan', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Yi Fan', 'EmailAddress': '[email protected]', 'NSF_ID': '000867576', 'StartDate': '08/15/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Northwestern University', 'CityName': 'EVANSTON', 'ZipCode': '602080001', 'PhoneNumber': '3125037955', 'StreetAddress': '633 CLARK ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Illinois', 'StateCode': 'IL', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_ORG': 'IL09', 'ORG_UEI_NUM': 'EXZVPWZBLUE8', 'ORG_LGL_BUS_NAME': 'NORTHWESTERN UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Northwestern University', 'CityName': 'EVANSTON', 'StateCode': 'IL', 'ZipCode': '602080001', 'StreetAddress': '633 CLARK ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Illinois', 'CountryFlag': '1', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_PERF': 'IL09'}
|
{'Code': '164200', 'Text': 'Special Initiatives'}
|
2024~448916
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2429545.xml'}
|
Collaborative Research: IGE: Track1: Caselet: Deliberate Practice with Scalable Case-based Learning to Enhance Data Science Problem Solving Competency
|
NSF
|
10/01/2024
|
09/30/2027
| 365,905 | 365,905 |
{'Value': 'Standard Grant'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Liz Webber', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924316'}
|
A sustainable society needs a diverse and competent workforce equipped with skills to extract patterns from large and complex datasets, turn them into actionable insights, and develop solutions to solve real-world problems relevant to society. With the advancement of generative artificial intelligence (AI), machines are increasingly capable of writing code according to specific instructions and performing specific data analysis tasks. Higher-order problem-solving skills are becoming increasingly important to develop among students as they are less likely to be replaced by AI. Thus, a scalable, innovative solution is urgently needed to help graduate students develop their critical-thinking skills. This National Science Foundation Innovations in Graduate Education (IGE) award to the University of Maryland Baltimore County (UMBC) and the University of Central Florida (UCF) will augment, refine, and pilot Caselet, a scalable case-based practice tool, by leveraging AI, machine learning, and data analytics approaches, including large language models (LLMs). This project will support development of data science problem-solving skills in both cognitive (the knowledge and skills themselves) and metacognitive domains (the skills for learning how to learn). The project will address the rapidly changing landscape of education in computing and data-intensive courses in terms of both “what we teach” and “how we teach.” <br/><br/>This project will augment and refine the Caselet practice tool in three dimensions to support scalable deployment and adoption through an iterative design and test framework. The research team will enhance the Caselet tool with new features, to be piloted and tested by up to 1000 students drawn from three graduate programs over a three-year period at the University of Maryland Baltimore County, a minority-serving institution. The project will focus on three tasks to address scale-up challenges. The first task will explore the approach to help scale up the authoring of Caselet using Large Language Model (LLMs). This approach aims to expedite the authoring process by identifying appropriate case studies and drafting relevant questions and explanations before submitting them for expert review. The second task aims to scale up the cognitive skills assessment in data science problem solving using machine learning models to track students’ skill mastery at a refined level of precision. The third task will focus on the scalable assessment of metacognitive competencies related to data science problem-solving through multichannel multimodal data collection in controlled lab environments and course-based and self-paced settings. Along with technology development, the research team will conduct pilot studies among UBMC graduate students from three different programs in various educational contexts, including online vs. in-person, instructor-led, or self-paced. In addition to the research findings, a guidebook will be created to support the adoption of Caselet by students and instructors from other educational institutions. The findings and pedagogically enhanced Caselet and associated data science problems stemming for this project will be disseminated to graduate-level faculty across UMBC, UCF, and other partnering institutions as well as scholarly conferences.<br/><br/>The Innovations in Graduate Education (IGE) program is focused on research in graduate education. The goals of IGE are to pilot, test and validate innovative approaches to graduate education and to generate the knowledge required to move these approaches into the broader community.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/29/2024
|
07/29/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2429590
|
[{'FirstName': 'Shimei', 'LastName': 'Pan', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Shimei Pan', 'EmailAddress': '[email protected]', 'NSF_ID': '000677258', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Lujie', 'LastName': 'Chen', 'PI_MID_INIT': 'K', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Lujie K Chen', 'EmailAddress': '[email protected]', 'NSF_ID': '000839143', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'University of Maryland Baltimore County', 'CityName': 'BALTIMORE', 'ZipCode': '212500001', 'PhoneNumber': '4104553140', 'StreetAddress': '1000 HILLTOP CIR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Maryland', 'StateCode': 'MD', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MD07', 'ORG_UEI_NUM': 'RNKYWXURFRL5', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF MARYLAND BALTIMORE COUNTY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Maryland Baltimore County', 'CityName': 'BALTIMORE', 'StateCode': 'MD', 'ZipCode': '212500001', 'StreetAddress': '1000 HILLTOP CIR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Maryland', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MD07'}
|
{'Code': '260Y00', 'Text': 'Innovations in Grad Education'}
|
2024~365905
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2429590.xml'}
|
Collaborative Research: IGE: Track1: Caselet: Deliberate Practice with Scalable Case-based Learning to Enhance Data Science Problem Solving Competency
|
NSF
|
10/01/2024
|
09/30/2027
| 134,000 | 134,000 |
{'Value': 'Standard Grant'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Liz Webber', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924316'}
|
A sustainable society needs a diverse and competent workforce equipped with skills to extract patterns from large and complex datasets, turn them into actionable insights, and develop solutions to solve real-world problems relevant to society. With the advancement of generative artificial intelligence (AI), machines are increasingly capable of writing code according to specific instructions and performing specific data analysis tasks. Higher-order problem-solving skills are becoming increasingly important to develop among students as they are less likely to be replaced by AI. Thus, a scalable, innovative solution is urgently needed to help graduate students develop their critical-thinking skills. This National Science Foundation Innovations in Graduate Education (IGE) award to the University of Maryland Baltimore County (UMBC) and the University of Central Florida (UCF) will augment, refine, and pilot Caselet, a scalable case-based practice tool, by leveraging AI, machine learning, and data analytics approaches, including large language models (LLMs). This project will support development of data science problem-solving skills in both cognitive (the knowledge and skills themselves) and metacognitive domains (the skills for learning how to learn). The project will address the rapidly changing landscape of education in computing and data-intensive courses in terms of both “what we teach” and “how we teach.” <br/><br/>This project will augment and refine the Caselet practice tool in three dimensions to support scalable deployment and adoption through an iterative design and test framework. The research team will enhance the Caselet tool with new features, to be piloted and tested by up to 1000 students drawn from three graduate programs over a three-year period at the University of Maryland Baltimore County, a minority-serving institution. The project will focus on three tasks to address scale-up challenges. The first task will explore the approach to help scale up the authoring of Caselet using Large Language Model (LLMs). This approach aims to expedite the authoring process by identifying appropriate case studies and drafting relevant questions and explanations before submitting them for expert review. The second task aims to scale up the cognitive skills assessment in data science problem solving using machine learning models to track students’ skill mastery at a refined level of precision. The third task will focus on the scalable assessment of metacognitive competencies related to data science problem-solving through multichannel multimodal data collection in controlled lab environments and course-based and self-paced settings. Along with technology development, the research team will conduct pilot studies among UBMC graduate students from three different programs in various educational contexts, including online vs. in-person, instructor-led, or self-paced. In addition to the research findings, a guidebook will be created to support the adoption of Caselet by students and instructors from other educational institutions. The findings and pedagogically enhanced Caselet and associated data science problems stemming for this project will be disseminated to graduate-level faculty across UMBC, UCF, and other partnering institutions as well as scholarly conferences.<br/><br/>The Innovations in Graduate Education (IGE) program is focused on research in graduate education. The goals of IGE are to pilot, test and validate innovative approaches to graduate education and to generate the knowledge required to move these approaches into the broader community.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/29/2024
|
07/29/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2429591
|
{'FirstName': 'Roger', 'LastName': 'Azevedo', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Roger Azevedo', 'EmailAddress': '[email protected]', 'NSF_ID': '000206946', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'The University of Central Florida Board of Trustees', 'CityName': 'ORLANDO', 'ZipCode': '328168005', 'PhoneNumber': '4078230387', 'StreetAddress': '4000 CENTRAL FLORIDA BLVD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Florida', 'StateCode': 'FL', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_ORG': 'FL10', 'ORG_UEI_NUM': 'RD7MXJV7DKT9', 'ORG_LGL_BUS_NAME': 'THE UNIVERSITY OF CENTRAL FLORIDA BOARD OF TRUSTEES', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'The University of Central Florida Board of Trustees', 'CityName': 'ORLANDO', 'StateCode': 'FL', 'ZipCode': '328168005', 'StreetAddress': '4000 CENTRAL FLORIDA BLVD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Florida', 'CountryFlag': '1', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_PERF': 'FL10'}
|
{'Code': '260Y00', 'Text': 'Innovations in Grad Education'}
|
2024~134000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2429591.xml'}
|
I-Corps: Translation Potential of Deployable, Electrostatically Actuated, Mesh Reflector Antennas for Satellite Applications
|
NSF
|
06/01/2024
|
05/31/2025
| 50,000 | 50,000 |
{'Value': 'Standard Grant'}
|
{'Code': '15030000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'TI', 'LongName': 'Translational Impacts'}}
|
{'SignBlockName': 'Molly Wasko', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924749'}
|
The broader impact of this I-Corps project is based on the development of electrostatic actuation technology for space satellite applications. This technology enables dynamic re-shaping of membrane reflectors for satellite applications on-orbit. This capability has the potential to expand flexibility in commercial satellite communications from geostationary orbit to cover different geographic areas, by allowing repurposing of existing satellites. The ability to reshape the reflector on-orbit allows for large reflectors with unprecedented surface precision to be used for innovative atmospheric radar instruments and improved weather monitoring from space. This technology could enable longer-range and more precise forecasting of tropical cyclones, helping protect coastal communities from storms.<br/><br/>This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. The solution is based on the development of electrostatic actuation of membrane reflectors for satellite applications. The research builds on a concept originally proposed in the 1980s for membrane reflectors, where a command surface of electrodes parallel to the controlled reflector surface is used to apply a bias voltage across the gap. The coulomb force is used to pull the flexible membrane into a dished reflector shape, and the voltage applied to each electrode can be controlled to change the focal length or steer and shape the reflector beam. Current versions of membrane reflectors for satellite applications are largely passive, and thus limited in flexibility. However, electrostatic actuation allows active beam steering and focal length shifting as well as surface control. This innovation enables electrostatic actuation integration into existing designs to expand the capabilities of membrane reflectors for satellites.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
05/28/2024
|
05/28/2024
|
None
|
Grant
|
47.084
|
1
|
4900
|
4900
|
2429600
|
{'FirstName': 'Zachary', 'LastName': 'Cordero', 'PI_MID_INIT': 'C', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Zachary C Cordero', 'EmailAddress': '[email protected]', 'NSF_ID': '000712525', 'StartDate': '05/28/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Massachusetts Institute of Technology', 'CityName': 'CAMBRIDGE', 'ZipCode': '021394301', 'PhoneNumber': '6172531000', 'StreetAddress': '77 MASSACHUSETTS AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MA07', 'ORG_UEI_NUM': 'E2NYLCDML6V1', 'ORG_LGL_BUS_NAME': 'MASSACHUSETTS INSTITUTE OF TECHNOLOGY', 'ORG_PRNT_UEI_NUM': 'E2NYLCDML6V1'}
|
{'Name': 'Massachusetts Institute of Technology', 'CityName': 'CAMBRIDGE', 'StateCode': 'MA', 'ZipCode': '021394301', 'StreetAddress': '77 MASSACHUSETTS AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MA07'}
|
{'Code': '802300', 'Text': 'I-Corps'}
|
2024~50000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2429600.xml'}
|
IGE: Track 2: Transforming Graduate STEM Education: A Study of a Data Science and AI Credential for STEM Doctoral Students
|
NSF
|
10/01/2024
|
09/30/2029
| 789,218 | 789,218 |
{'Value': 'Standard Grant'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Daniel Denecke', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928072'}
|
This National Science Foundation Innovations of Graduate Education (IGE) Track 2 award to the University of Chicago will support the creation of a data science credential that will enable STEM doctoral students to apply data science (DS) and artificial intelligence (AI) in their fields. The methods and tools of data science are crucial for all scientific domains, and AI and machine learning will support future advances in all disciplines by providing researchers with tools to explore new and more complex questions of importance to society. There has been limited research on formal mechanisms for creating integrative opportunities between DS/AI and other STEM disciplines or on the role that a credential from another discipline can play in STEM graduate students’ career paths and research. This new data science credential will enable STEM doctoral students to learn how to use data and AI accurately and responsibly and understand its broader impacts on social systems, make and critique data backed arguments, and become fluent in the latest computation tools. Moreover, the project will contribute to knowledge in these areas by focusing on doctoral students in STEM disciplines outside of data science (e.g. astrophysics, geophysical sciences, genetics, engineering, neuroscience). <br/><br/>With support from their advisors, second- and third-year graduate students will enroll in three customized core courses during which they will consider ways to apply DS and AI concepts in their disciplines. They will then complete a fourth culminating course residing in their home department and focus on applying DS/AI in their own research. Students will also participate in co-curricular activities to support their professional growth. The research activities will use a mixed methods design to focus on three areas: (a) the role that participation in the credential program plays on shifting disciplinary perspectives; (b) the role that participation in the credential program plays in graduate students’ job search and career direction; and (c) the institutional and systemic processes needed to establish and implement an interdisciplinary credential and the role that credential plays in shifting institutional culture. Separate evaluation questions will inform project and course improvement through a continuous learning process.<br/><br/>The Innovations in Graduate Education (IGE) program is focused on research in graduate education. The goals of IGE are to pilot, test and validate innovative approaches to graduate education and to generate the knowledge required to move these approaches into the broader community.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/08/2024
|
08/08/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2429605
|
[{'FirstName': 'Jeanne', 'LastName': 'Century', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jeanne Century', 'EmailAddress': '[email protected]', 'NSF_ID': '000308155', 'StartDate': '08/08/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Dan', 'LastName': 'Nicolae', 'PI_MID_INIT': 'L', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Dan L Nicolae', 'EmailAddress': '[email protected]', 'NSF_ID': '000297028', 'StartDate': '08/08/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Joanna', 'LastName': 'Schiffman', 'PI_MID_INIT': 'G', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Joanna G Schiffman', 'EmailAddress': '[email protected]', 'NSF_ID': '000943149', 'StartDate': '08/08/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'University of Chicago', 'CityName': 'CHICAGO', 'ZipCode': '606375418', 'PhoneNumber': '7737028669', 'StreetAddress': '5801 S ELLIS AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Illinois', 'StateCode': 'IL', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'IL01', 'ORG_UEI_NUM': 'ZUE9HKT2CLC9', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CHICAGO', 'ORG_PRNT_UEI_NUM': 'ZUE9HKT2CLC9'}
|
{'Name': 'University of Chicago', 'CityName': 'CHICAGO', 'StateCode': 'IL', 'ZipCode': '606375418', 'StreetAddress': '5801 S ELLIS AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Illinois', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'IL01'}
|
{'Code': '260Y00', 'Text': 'Innovations in Grad Education'}
|
2024~789218
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2429605.xml'}
|
IGE: Track 2: Mobilizing Community Cultural Wealth to Transform STEM Graduate Education
|
NSF
|
10/01/2024
|
09/30/2028
| 999,985 | 999,985 |
{'Value': 'Standard Grant'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Daniel Denecke', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928072'}
|
Gaps in equity and inclusion within STEM graduate education in the U.S. persist. At stake is the loss of contributions toward scientific innovation and excellence from more racially and economically diverse scientists (e.g., low-income, first-generation, students of color). Indeed, these students bring various cultural strengths from their home communities that can transform learning spaces, known as community cultural wealth. However, the transformative power of their cultural wealth is only possible with institutional commitment to recognize its value, including the implementation of educational practices that take concrete steps to leverage these diverse strengths with a critical lens. This National Science Foundation Innovations of Graduate Education (IGE) Track 2 award to the University of California, Santa Cruz will conduct a multi-stage and multi-program intervention aimed at investigating how programs build structural opportunities and support for mobilizing marginalized doctoral students’ cultural strengths and ways of knowing. Using a multiple case study design to understand the mobilization process, this project will illuminate pathways for diversifying, strengthening, and transforming STEM graduate education to better represent and serve new generations of talented scientists.<br/><br/>The project will take inventory of a fellowship support program (Cota Robles Fellows program), an interdisciplinary research training program (New Gen Learning Consortium), and a mentoring training program (Equity-Minded Mentoring Certificate program). The goal is to redesign program elements to better mobilize marginalized students’ strengths for learning and make crucial connections to home departments to scale culture changes in STEM graduate education at the institutional level. In Stage 1, the project will connect to home departments and gather baseline data to examine the strengths and gaps of the three focal programs. Stage 2 will focus on relationship-building between programs and home departments, including learning about the specific cultures of support for graduate students and identifying potential target areas for collaboration. This step includes presenting the mobilization framework and findings from Stage 1 to develop re-design plans. Stage 3 will focus on implementing the re-design plans. The project will use a multiple case study design to examine the implementation process through focus groups with program staff and department contacts to examine their perspectives, challenges, and questions about the implementation as it unfolds and as it relates to the mobilization process, paying keen attention to concrete steps taken and resources used toward mobilization. In Stage 4, the project will study the impacts of the implementation on the culture, practices, and support structures of the programs and department spaces in the longer term, including a final focus group to have program staff and department contacts reflect on the implementation process, again paying keen attention to questions related to the mobilization process. Findings will be disseminated through conference presentations, brief reports, and publications on lessons learned for universities, researchers, and practitioners to scale up the impacts of the project.<br/><br/>The Innovations in Graduate Education (IGE) program is focused on research in graduate education. The goals of IGE are to pilot, test and validate innovative approaches to graduate education and to generate the knowledge required to move these approaches into the broader community.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/05/2024
|
08/05/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2429624
|
[{'FirstName': 'Su-hua', 'LastName': 'Wang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Su-hua Wang', 'EmailAddress': '[email protected]', 'NSF_ID': '000312722', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Enrico', 'LastName': 'Ramirez-Ruiz', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Enrico J Ramirez-Ruiz', 'EmailAddress': '[email protected]', 'NSF_ID': '000198783', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Rebecca', 'LastName': 'Covarrubias', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Rebecca Covarrubias', 'EmailAddress': '[email protected]', 'NSF_ID': '000719928', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'University of California-Santa Cruz', 'CityName': 'SANTA CRUZ', 'ZipCode': '950641077', 'PhoneNumber': '8314595278', 'StreetAddress': '1156 HIGH ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '19', 'CONGRESS_DISTRICT_ORG': 'CA19', 'ORG_UEI_NUM': 'VXUFPE4MCZH5', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CALIFORNIA SANTA CRUZ', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of California-Santa Cruz', 'CityName': 'SANTA CRUZ', 'StateCode': 'CA', 'ZipCode': '950641077', 'StreetAddress': '1156 HIGH ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '19', 'CONGRESS_DISTRICT_PERF': 'CA19'}
|
{'Code': '260Y00', 'Text': 'Innovations in Grad Education'}
|
2024~999985
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2429624.xml'}
|
Collaborative Research: IGE: Track 2: SciComm LIFT: Leveraging Institutional capacity for eFfective graduate student Training
|
NSF
|
10/01/2024
|
09/30/2028
| 742,253 | 742,253 |
{'Value': 'Standard Grant'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Daniel Denecke', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928072'}
|
Communication is the top job skill required across all sectors, and ethical science communication (scicomm) helps scientists identify and engage with the values, needs, and diverse ways of knowing of people ranging from community members to policy makers. Graduate students themselves have identified the need for training in these translational skills before embarking on their post-graduation careers. Yet, most scientists receive no formal training in scicomm and report feeling ill-equipped to share science effectively. Scicomm training is not widely embraced in academia due to systemic barriers that impede and devalue both study and training in scicomm. Working at an unprecedented scale, SciComm LIFT will survey, train, and support thousands of graduate students — across the country and across institution types — for the top skills required by employers: oral and written communication and collaboration. SciComm LIFT’s emphasis on ethical scicomm training will also directly enhance graduate degree programs and professional development programs, ensuring early career scientists are more capable of doing and sharing science in ways that meet the needs of society and foster public trust in and of science.<br/><br/>SciComm LIFT uses expectancy values theory to address three issues: (1) most scicomm training programs prioritize knowledge gains and skills, but ignore the human/ethical elements of scicomm that are vital to science that fosters public trust; (2) existing scicomm training is rarely assessed, making it difficult for trainers and programs to optimize programming and demonstrate its efficacy; (3) long-standing, systemic barriers impede integration of ethical scicomm training. In Aim 1, SciComm LIFT will conduct a broadly distributed, systems-scoping survey (Motivations to Engage in Scicomm Advancement; MESA) of graduate students, faculty, and staff to (1) assess current knowledge, motivations, and self-efficacy around ethical scicomm and (2) quantify the extent of training addressing ethical dimensions of scicomm. MESA will be made available to the research and graduate education community as a validated, reliable instrument tested across contexts and institutions. Aim 2 is a multi-institutional study to gauge the impact of three ethical scicomm interventions in graduate programs, which will provide much-needed data that can be used to calibrate scicomm training programs nationwide. Aim 3 investigates how three levels of coaching can support academic faculty and staff to overcome institutional barriers preventing them from offering ethical scicomm training to graduate students. These aims will benefit society by preparing graduate students to bridge the divide between science and society through effective, ethical communication.<br/><br/>The Innovations in Graduate Education (IGE) program is focused on research in graduate education. The goals of IGE are to pilot, test and validate innovative approaches to graduate education and to generate the knowledge required to move these approaches into the broader community.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/05/2024
|
08/05/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2429657
|
{'FirstName': 'Bethann', 'LastName': 'Merkle', 'PI_MID_INIT': 'G', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Bethann G Merkle', 'EmailAddress': '[email protected]', 'NSF_ID': '000822707', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Wyoming', 'CityName': 'LARAMIE', 'ZipCode': '820712000', 'PhoneNumber': '3077665320', 'StreetAddress': '1000 E UNIVERSITY AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Wyoming', 'StateCode': 'WY', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_ORG': 'WY00', 'ORG_UEI_NUM': 'FDR5YF2K32X5', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF WYOMING', 'ORG_PRNT_UEI_NUM': 'FDR5YF2K32X5'}
|
{'Name': 'University of Wyoming', 'CityName': 'LARAMIE', 'StateCode': 'WY', 'ZipCode': '820712000', 'StreetAddress': '1000 E UNIVERSITY AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Wyoming', 'CountryFlag': '1', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_PERF': 'WY00'}
|
{'Code': '260Y00', 'Text': 'Innovations in Grad Education'}
|
2024~742253
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2429657.xml'}
|
Collaborative Research: IGE: Track 2: SciComm LIFT: Leveraging Institutional capacity for eFfective graduate student Training
|
NSF
|
10/01/2024
|
09/30/2028
| 73,362 | 73,362 |
{'Value': 'Standard Grant'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Daniel Denecke', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928072'}
|
Communication is the top job skill required across all sectors, and ethical science communication (scicomm) helps scientists identify and engage with the values, needs, and diverse ways of knowing of people ranging from community members to policy makers. Graduate students themselves have identified the need for training in these translational skills before embarking on their post-graduation careers. Yet, most scientists receive no formal training in scicomm and report feeling ill-equipped to share science effectively. Scicomm training is not widely embraced in academia due to systemic barriers that impede and devalue both study and training in scicomm. Working at an unprecedented scale, SciComm LIFT will survey, train, and support thousands of graduate students — across the country and across institution types — for the top skills required by employers: oral and written communication and collaboration. SciComm LIFT’s emphasis on ethical scicomm training will also directly enhance graduate degree programs and professional development programs, ensuring early career scientists are more capable of doing and sharing science in ways that meet the needs of society and foster public trust in and of science.<br/><br/>SciComm LIFT uses expectancy values theory to address three issues: (1) most scicomm training programs prioritize knowledge gains and skills, but ignore the human/ethical elements of scicomm that are vital to science that fosters public trust; (2) existing scicomm training is rarely assessed, making it difficult for trainers and programs to optimize programming and demonstrate its efficacy; (3) long-standing, systemic barriers impede integration of ethical scicomm training. In Aim 1, SciComm LIFT will conduct a broadly distributed, systems-scoping survey (Motivations to Engage in Scicomm Advancement; MESA) of graduate students, faculty, and staff to (1) assess current knowledge, motivations, and self-efficacy around ethical scicomm and (2) quantify the extent of training addressing ethical dimensions of scicomm. MESA will be made available to the research and graduate education community as a validated, reliable instrument tested across contexts and institutions. Aim 2 is a multi-institutional study to gauge the impact of three ethical scicomm interventions in graduate programs, which will provide much-needed data that can be used to calibrate scicomm training programs nationwide. Aim 3 investigates how three levels of coaching can support academic faculty and staff to overcome institutional barriers preventing them from offering ethical scicomm training to graduate students. These aims will benefit society by preparing graduate students to bridge the divide between science and society through effective, ethical communication.<br/><br/>The Innovations in Graduate Education (IGE) program is focused on research in graduate education. The goals of IGE are to pilot, test and validate innovative approaches to graduate education and to generate the knowledge required to move these approaches into the broader community.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/05/2024
|
08/05/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2429658
|
{'FirstName': 'E Dale', 'LastName': 'Broder', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'E Dale Broder', 'EmailAddress': '[email protected]', 'NSF_ID': '000881522', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'American University', 'CityName': 'WASHINGTON', 'ZipCode': '200168002', 'PhoneNumber': '2028853440', 'StreetAddress': '4400 MASSACHUSETTS AVE NW', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'District of Columbia', 'StateCode': 'DC', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_ORG': 'DC00', 'ORG_UEI_NUM': 'H4VNDUN2VWU5', 'ORG_LGL_BUS_NAME': 'AMERICAN UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'American University', 'CityName': 'WASHINGTON', 'StateCode': 'DC', 'ZipCode': '200168002', 'StreetAddress': '4400 MASSACHUSETTS AVE NW', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'District of Columbia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_PERF': 'DC00'}
|
{'Code': '260Y00', 'Text': 'Innovations in Grad Education'}
|
2024~73362
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2429658.xml'}
|
Collaborative Research: IGE: Track 2: SciComm LIFT: Leveraging Institutional capacity for eFfective graduate student Training
|
NSF
|
10/01/2024
|
09/30/2028
| 89,783 | 89,783 |
{'Value': 'Standard Grant'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Daniel Denecke', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928072'}
|
Communication is the top job skill required across all sectors, and ethical science communication (scicomm) helps scientists identify and engage with the values, needs, and diverse ways of knowing of people ranging from community members to policy makers. Graduate students themselves have identified the need for training in these translational skills before embarking on their post-graduation careers. Yet, most scientists receive no formal training in scicomm and report feeling ill-equipped to share science effectively. Scicomm training is not widely embraced in academia due to systemic barriers that impede and devalue both study and training in scicomm. Working at an unprecedented scale, SciComm LIFT will survey, train, and support thousands of graduate students — across the country and across institution types — for the top skills required by employers: oral and written communication and collaboration. SciComm LIFT’s emphasis on ethical scicomm training will also directly enhance graduate degree programs and professional development programs, ensuring early career scientists are more capable of doing and sharing science in ways that meet the needs of society and foster public trust in and of science.<br/><br/>SciComm LIFT uses expectancy values theory to address three issues: (1) most scicomm training programs prioritize knowledge gains and skills, but ignore the human/ethical elements of scicomm that are vital to science that fosters public trust; (2) existing scicomm training is rarely assessed, making it difficult for trainers and programs to optimize programming and demonstrate its efficacy; (3) long-standing, systemic barriers impede integration of ethical scicomm training. In Aim 1, SciComm LIFT will conduct a broadly distributed, systems-scoping survey (Motivations to Engage in Scicomm Advancement; MESA) of graduate students, faculty, and staff to (1) assess current knowledge, motivations, and self-efficacy around ethical scicomm and (2) quantify the extent of training addressing ethical dimensions of scicomm. MESA will be made available to the research and graduate education community as a validated, reliable instrument tested across contexts and institutions. Aim 2 is a multi-institutional study to gauge the impact of three ethical scicomm interventions in graduate programs, which will provide much-needed data that can be used to calibrate scicomm training programs nationwide. Aim 3 investigates how three levels of coaching can support academic faculty and staff to overcome institutional barriers preventing them from offering ethical scicomm training to graduate students. These aims will benefit society by preparing graduate students to bridge the divide between science and society through effective, ethical communication.<br/><br/>The Innovations in Graduate Education (IGE) program is focused on research in graduate education. The goals of IGE are to pilot, test and validate innovative approaches to graduate education and to generate the knowledge required to move these approaches into the broader community.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/05/2024
|
08/05/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2429659
|
{'FirstName': 'Robin', 'LastName': 'Tinghitella', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Robin Tinghitella', 'EmailAddress': '[email protected]', 'NSF_ID': '000582856', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Denver', 'CityName': 'DENVER', 'ZipCode': '802104711', 'PhoneNumber': '3038712000', 'StreetAddress': '2199 S UNIVERSITY BLVD RM 222', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Colorado', 'StateCode': 'CO', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'CO01', 'ORG_UEI_NUM': 'WCUGNQQ8DZU1', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF DENVER', 'ORG_PRNT_UEI_NUM': 'WCUGNQQ8DZU1'}
|
{'Name': 'University of Denver', 'CityName': 'DENVER', 'StateCode': 'CO', 'ZipCode': '802104711', 'StreetAddress': '2199 S UNIVERSITY BLVD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Colorado', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'CO01'}
|
{'Code': '260Y00', 'Text': 'Innovations in Grad Education'}
|
2024~89783
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2429659.xml'}
|
Collaborative Research: IGE: Track 2: SciComm LIFT: Leveraging Institutional capacity for eFfective graduate student Training
|
NSF
|
10/01/2024
|
09/30/2028
| 94,602 | 94,602 |
{'Value': 'Standard Grant'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Daniel Denecke', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928072'}
|
Communication is the top job skill required across all sectors, and ethical science communication (scicomm) helps scientists identify and engage with the values, needs, and diverse ways of knowing of people ranging from community members to policy makers. Graduate students themselves have identified the need for training in these translational skills before embarking on their post-graduation careers. Yet, most scientists receive no formal training in scicomm and report feeling ill-equipped to share science effectively. Scicomm training is not widely embraced in academia due to systemic barriers that impede and devalue both study and training in scicomm. Working at an unprecedented scale, SciComm LIFT will survey, train, and support thousands of graduate students — across the country and across institution types — for the top skills required by employers: oral and written communication and collaboration. SciComm LIFT’s emphasis on ethical scicomm training will also directly enhance graduate degree programs and professional development programs, ensuring early career scientists are more capable of doing and sharing science in ways that meet the needs of society and foster public trust in and of science.<br/><br/>SciComm LIFT uses expectancy values theory to address three issues: (1) most scicomm training programs prioritize knowledge gains and skills, but ignore the human/ethical elements of scicomm that are vital to science that fosters public trust; (2) existing scicomm training is rarely assessed, making it difficult for trainers and programs to optimize programming and demonstrate its efficacy; (3) long-standing, systemic barriers impede integration of ethical scicomm training. In Aim 1, SciComm LIFT will conduct a broadly distributed, systems-scoping survey (Motivations to Engage in Scicomm Advancement; MESA) of graduate students, faculty, and staff to (1) assess current knowledge, motivations, and self-efficacy around ethical scicomm and (2) quantify the extent of training addressing ethical dimensions of scicomm. MESA will be made available to the research and graduate education community as a validated, reliable instrument tested across contexts and institutions. Aim 2 is a multi-institutional study to gauge the impact of three ethical scicomm interventions in graduate programs, which will provide much-needed data that can be used to calibrate scicomm training programs nationwide. Aim 3 investigates how three levels of coaching can support academic faculty and staff to overcome institutional barriers preventing them from offering ethical scicomm training to graduate students. These aims will benefit society by preparing graduate students to bridge the divide between science and society through effective, ethical communication.<br/><br/>The Innovations in Graduate Education (IGE) program is focused on research in graduate education. The goals of IGE are to pilot, test and validate innovative approaches to graduate education and to generate the knowledge required to move these approaches into the broader community.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/05/2024
|
08/05/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2429660
|
{'FirstName': 'Meena', 'LastName': 'Balgopal', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Meena M Balgopal', 'EmailAddress': '[email protected]', 'NSF_ID': '000522519', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Colorado State University', 'CityName': 'FORT COLLINS', 'ZipCode': '805212807', 'PhoneNumber': '9704916355', 'StreetAddress': '601 S HOWES ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Colorado', 'StateCode': 'CO', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'CO02', 'ORG_UEI_NUM': 'LT9CXX8L19G1', 'ORG_LGL_BUS_NAME': 'COLORADO STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Colorado State University', 'CityName': 'FORT COLLINS', 'StateCode': 'CO', 'ZipCode': '805214593', 'StreetAddress': '200 W. Lake St.', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Colorado', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'CO02'}
|
{'Code': '260Y00', 'Text': 'Innovations in Grad Education'}
|
2024~94602
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2429660.xml'}
|
ReDDDoT Phase 2: Leveraging Urban AI as a Communal Tool for Connection and Exchange in Harlem
|
NSF
|
10/01/2024
|
09/30/2027
| 1,447,662 | 1,447,662 |
{'Value': 'Standard Grant'}
|
{'Code': '15020000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'ITE', 'LongName': 'Innovation and Technology Ecosystems'}}
|
{'SignBlockName': 'Danielle F. Sumy', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924217'}
|
Cities are at a technological crossroads. While the rise of generative Artificial Intelligence (AI) promises to reshape how urban residents inhabit, study, work, and conduct their daily lives, adopting cutting-edge technology into socially complex and high-stakes scenarios carries enormous risks. It provides fertile ground for a crisis of public trust in institutions, experts, and technology. Because AI is a particularly abstract and inscrutable “black box,” we offer an approach that fundamentally reimagines what a responsible co-design process for urban AI could be. At the center of this work is the creation of a new “Citizen AI,” built from the bottom up and as the culmination of a plurality of voices, experiences, and forms of expertise. The project team, The Trust Collaboratory (TC), and the Gen-4 NSF Center for Smart Streetscapes (CS3) at Columbia University, together with over ten community-based organizations in Harlem, will create a process toward local use cases of urban AI based on community-driven privacy, safety, reliability, and transparency parameters. At the center of this process will be the co-creation of a community-based conversational engagement tool (teLLMe) that redefines how, when, by whom, and under what conditions AI should be integrated into New York City and its social fabric.<br/><br/>AI can play an integral role in how urban residents will inhabit and navigate future cities. This requires that AI designers prioritize their intended users and their needs. To achieve this vision of an urban AI serving the common good, this project presents a complete and self-sustained implementation lifecycle to create a “Citizen AI.” At the center of this process will be the co-creation of a community-based conversational engagement tool (teLLMe) that redefines how, when, by whom, and under what conditions AI should be integrated into our city and its social fabric. This LLM-based system will elevate the principle that responsibly designed urban AI requires modes of technology co-production that bring civic organizations, advocacy groups, small businesses, domain experts, and residents under one umbrella. The team's approach draws on a recent “participatory turn” that goes beyond mere assurances of data security and efforts toward explainability. This co-design sequence will proceed side by side with research on the social dynamics of trusting behavior as well as contributions from engineers and data scientists with expertise in accessibility, data privacy, machine learning, and computer vision to make AI accountable, fair, safe, transparent, and trusted.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/20/2024
|
08/20/2024
|
None
|
Grant
|
47.084
|
1
|
4900
|
4900
|
2429672
|
[{'FirstName': 'Gil', 'LastName': 'Eyal', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Gil Eyal', 'EmailAddress': '[email protected]', 'NSF_ID': '000490537', 'StartDate': '08/20/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Rachel', 'LastName': 'Cummings', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Rachel Cummings', 'EmailAddress': '[email protected]', 'NSF_ID': '000750751', 'StartDate': '08/20/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Carl', 'LastName': 'Vondrick', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Carl M Vondrick', 'EmailAddress': '[email protected]', 'NSF_ID': '000755733', 'StartDate': '08/20/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Jorge', 'LastName': 'Ortiz', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jorge J Ortiz', 'EmailAddress': '[email protected]', 'NSF_ID': '000776600', 'StartDate': '08/20/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Brian', 'LastName': 'Smith', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Brian A Smith', 'EmailAddress': '[email protected]', 'NSF_ID': '000836673', 'StartDate': '08/20/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Columbia University', 'CityName': 'NEW YORK', 'ZipCode': '100277922', 'PhoneNumber': '2128546851', 'StreetAddress': '615 W 131ST ST', 'StreetAddress2': 'MC 8741', 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '13', 'CONGRESS_DISTRICT_ORG': 'NY13', 'ORG_UEI_NUM': 'F4N1QNPB95M4', 'ORG_LGL_BUS_NAME': 'THE TRUSTEES OF COLUMBIA UNIVERSITY IN THE CITY OF NEW YORK', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Columbia University', 'CityName': 'NEW YORK', 'StateCode': 'NY', 'ZipCode': '100277922', 'StreetAddress': '615 W 131ST ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '13', 'CONGRESS_DISTRICT_PERF': 'NY13'}
|
{'Code': '293Y00', 'Text': 'ReDDDoT-Resp Des Dev & Dp Tech'}
|
2024~1447662
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2429672.xml'}
|
Conference: Plant Scholars Program - Supporting Exceptional Talent to Solve 21st Century Agricultural Problems
|
NSF
|
06/01/2024
|
05/31/2026
| 49,607 | 49,607 |
{'Value': 'Standard Grant'}
|
{'Code': '08090000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'IOS', 'LongName': 'Division Of Integrative Organismal Systems'}}
|
{'SignBlockName': 'Diane Jofuku Okamuro', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924508'}
|
By 2050, the global population will exceed 10 billion, and this population will experience a hotter, drier climate, reduced agricultural productivity, and prevalent food insecurity. Although these future conditions will impact the entire population, they will disproportionately impact impoverished communities, people of color, the Global South, and other marginalized groups. Many of the solutions to mitigate the impact of extreme environments will come from the plant science community. However, to realize the potential of plant research, intensive national and global collaborations among industry, academia, and government are required as well as a community of plant scientists that can adeptly communicate with the general public about agricultural problems across massive dimensions of scale. NSF funds will be used to support activities designed to broaden participation of faculty and students at institutions with minimal or limited research infrastructure at the annual Plant Biology (PB) 2024 conference and associated regional meetings sponsored and organized by the American Society of Plant Biologists (ASPB). Conference activities are designed to enhance participation and to introduce these scientists to research resources and funding opportunities that will help them connect to the broader plant biology research community year-round. <br/><br/>ASPB is a leader in supporting career development opportunities for a wide variety of scientists and is uniquely positioned to contribute toward the goal of creating a more inclusive plant science community and building bridges between scientists and the general public. With NSF support, two programs will be developed and implemented in conjunction with the annual ASPB conference June 22–26, 2024 (Honolulu, HI). Plant Science Saturday has been implemented at the last two national conferences and provides a unique opportunity for plant scientists to interact with the general public. This community event uses hands-on activities to engage families, particularly those with younger children, as a way to spark curiosity and build awareness of how plants positively impact economies, environments, and health. The aim of the Plant Scholars program is to create annual cohorts of constituents that are under-represented in plant biology across multiple axes of diversity (gender, racial/ethnic identity, institution type, etc.) at traditionally 'leaky' transition points in research education and career pathways. Cohorts will receive financial support to attend an ASPB conference and will be connected by networking prior to, during and following the conference, with the group growing yearly with each additional cohort. Supported scientists will be organized into cohorts spanning multiple career stages, promoting mentoring and collaboration. Additionally, professional development and scientific programming will be developed to address challenges faced by subgroups within the cohorts, with this programming being disseminated to all conference attendees and beyond.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
06/05/2024
|
06/05/2024
|
None
|
Grant
|
47.074
|
1
|
4900
|
4900
|
2429679
|
[{'FirstName': 'Crispin', 'LastName': 'Taylor', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Crispin Taylor', 'EmailAddress': '[email protected]', 'NSF_ID': '000329131', 'StartDate': '06/05/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Amanda', 'LastName': 'Storm', 'PI_MID_INIT': 'R', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Amanda R Storm', 'EmailAddress': '[email protected]', 'NSF_ID': '000911492', 'StartDate': '06/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Erin', 'LastName': 'Friedman', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Erin J Friedman', 'EmailAddress': '[email protected]', 'NSF_ID': '000689988', 'StartDate': '06/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'American Society of Plant Biologists', 'CityName': 'ROCKVILLE', 'ZipCode': '208552753', 'PhoneNumber': '3012960925', 'StreetAddress': '15501 MONONA DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Maryland', 'StateCode': 'MD', 'CONGRESSDISTRICT': '08', 'CONGRESS_DISTRICT_ORG': 'MD08', 'ORG_UEI_NUM': 'ER16NUB2ANX6', 'ORG_LGL_BUS_NAME': 'AMERICAN SOCIETY OF PLANT BIOLOGISTS', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'American Society of Plant Biologists', 'CityName': 'ROCKVILLE', 'StateCode': 'MD', 'ZipCode': '208552753', 'StreetAddress': '15501 MONONA DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Maryland', 'CountryFlag': '1', 'CONGRESSDISTRICT': '08', 'CONGRESS_DISTRICT_PERF': 'MD08'}
|
{'Code': '132900', 'Text': 'Plant Genome Research Project'}
|
2024~49607
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2429679.xml'}
|
ReDDDoT Phase 2: Responsible Multi-Modal AI Systems for Multi-Hazard Resilience and Situational Awareness
|
NSF
|
10/01/2024
|
09/30/2027
| 1,500,000 | 1,500,000 |
{'Value': 'Standard Grant'}
|
{'Code': '15020000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'ITE', 'LongName': 'Innovation and Technology Ecosystems'}}
|
{'SignBlockName': 'Danielle F. Sumy', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924217'}
|
Coastal storms and climate change, aging infrastructure, and rapid urbanization pose increasing risks to coastal communities. Institutions charged with supporting communities before, during, and following storm events require reliable and timely information on current and forecasted hydrometeorological conditions and infrastructure impacts, including roadway access and potential natural hazards-triggered technological incidents. Recent focus groups and structured interviews with emergency response organizations have revealed both the lack of integrated information sources and the lack of trusted, timely, and scientifically sound technology available to support situational awareness of compound hazard events and their anticipated impacts on infrastructure, a deficiency that hampers decision-making and response efforts. This project will design, develop, and deploy OpenSafe.AI, a framework that advances communities’ ability to reliably sense current conditions and forecast potential hazards and infrastructure impacts. This information is critical to inform response and recovery actions targeted at public health and safety and enhanced community resilience to coastal storm events. Working in concert with emergency response agencies in the Houston-Galveston area, we will not only iteratively design and tailor such a system, but probe transferability and scalability, design robustness, and data and model equity across diverse communities, including those that are under-resourced and under-served.<br/><br/>This project combines expertise in hazard and infrastructure resilience modeling, user-centered design, and responsible AI to revolutionize intelligent systems for situational awareness and scenario exploration under multiple compound coastal hazards. This convergent research will address the technical, theoretical, and methodological gaps in responsibly designing and developing situational awareness tools to support emergency response actions and risk mitigation interventions during tropical cyclones and coastal storm events. With an overarching user-centered design approach, it will pioneer responsible design strategies to enable (1) equitable and fair, (2) reliable and safe, (3) human-centered applications of AI in the disaster resilience domain. Along the way, the team will develop multi-modal foundation models that gain insights from a combination of physics-based, data-driven, and human-in-the-loop sources, and will advance methods to detect and largely overcome systemic bias, paucity of real-time data, and equity issues in models and data to promote equitable and fair situational awareness. As a result, the OpenSafe.AI framework pursues estimates of near-real time conditions and short-range forecasts (e.g., hours to days in advance) of multi-hazards (e.g., wind, wave, compound flooding) and their impacts on the built environment (e.g., damage hampering access to critical facilities or yielding hazardous material spills), thereby affording practical, timely, and equitable situational awareness.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/22/2024
|
08/22/2024
|
None
|
Grant
|
47.050, 47.084
|
1
|
4900
|
4900
|
2429680
|
[{'FirstName': 'Jamie', 'LastName': 'Padgett', 'PI_MID_INIT': 'E', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jamie E Padgett', 'EmailAddress': '[email protected]', 'NSF_ID': '000482836', 'StartDate': '08/22/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Xia', 'LastName': 'Hu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Xia Hu', 'EmailAddress': '[email protected]', 'NSF_ID': '000703493', 'StartDate': '08/22/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'David', 'LastName': 'Retchless', 'PI_MID_INIT': 'P', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'David P Retchless', 'EmailAddress': '[email protected]', 'NSF_ID': '000737459', 'StartDate': '08/22/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Avantika', 'LastName': 'Gori', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Avantika Gori', 'EmailAddress': '[email protected]', 'NSF_ID': '000989768', 'StartDate': '08/22/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'William Marsh Rice University', 'CityName': 'Houston', 'ZipCode': '770051827', 'PhoneNumber': '7133484820', 'StreetAddress': '6100 MAIN ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Texas', 'StateCode': 'TX', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_ORG': 'TX09', 'ORG_UEI_NUM': 'K51LECU1G8N3', 'ORG_LGL_BUS_NAME': 'WILLIAM MARSH RICE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'William Marsh Rice University', 'CityName': 'Houston', 'StateCode': 'TX', 'ZipCode': '770051827', 'StreetAddress': '6100 MAIN ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Texas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_PERF': 'TX09'}
|
[{'Code': '293Y00', 'Text': 'ReDDDoT-Resp Des Dev & Dp Tech'}, {'Code': '302Y00', 'Text': 'NSF-Ford Foundation Partnrshp'}]
|
2024~1500000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2429680.xml'}
|
I-Corps: Translation Potential of Accelerated and Energy-Efficient 3D Printing of High-Performance Polymers and Composites
|
NSF
|
07/01/2024
|
12/31/2024
| 50,000 | 50,000 |
{'Value': 'Standard Grant'}
|
{'Code': '15030000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'TI', 'LongName': 'Translational Impacts'}}
|
{'SignBlockName': 'Molly Wasko', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924749'}
|
The broader impact of this I-Corps project is based on the development of innovative fused filament fabrication (FFF) systems that can print high-performance thermoplastics with superior interlayer adhesion at high rates. A thermoplastic any plastic that becomes pliable or moldable at elevated temperatures and solidifies upon cooling. This technology has the potential to improve the additive manufacturing industry, valued at approximately $20 billion, by addressing critical market gaps and setting new standards for manufacturing robust and reliable components. The innovation will particularly benefit industries such as aerospace, automotive, and medical devices, which require stringent performance requirements.<br/><br/>This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. The solution is based on the development of new filament materials and heating methods that addresses the limitations of existing fused filament fabrication (FFF) technologies that can print high-performance thermoplastics with superior interlayer adhesion at high rates. The project aims to validate the market need for improved FFF systems through extensive customer discovery and analysis. The project's outcomes will guide subsequent stages of product development and inform a go-to-market strategy, ultimately driving broader adoption of FFF systems and capturing a larger share of the additive manufacturing market.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
06/25/2024
|
06/25/2024
|
None
|
Grant
|
47.084
|
1
|
4900
|
4900
|
2429715
|
{'FirstName': 'Mehran', 'LastName': 'Tehrani', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Mehran Tehrani', 'EmailAddress': '[email protected]', 'NSF_ID': '000651616', 'StartDate': '06/25/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of California-San Diego', 'CityName': 'LA JOLLA', 'ZipCode': '920930021', 'PhoneNumber': '8585344896', 'StreetAddress': '9500 GILMAN DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '50', 'CONGRESS_DISTRICT_ORG': 'CA50', 'ORG_UEI_NUM': 'UYTTZT6G9DT1', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CALIFORNIA, SAN DIEGO', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of California-San Diego', 'CityName': 'LA JOLLA', 'StateCode': 'CA', 'ZipCode': '920930021', 'StreetAddress': '9500 GILMAN DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '50', 'CONGRESS_DISTRICT_PERF': 'CA50'}
|
{'Code': '802300', 'Text': 'I-Corps'}
|
2024~50000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2429715.xml'}
|
IGE: Track 2: Cultivating an Indigenous Graduate Research Environment to Enhance Retention and Scientific Careers
|
NSF
|
10/01/2024
|
09/30/2028
| 999,864 | 999,864 |
{'Value': 'Standard Grant'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Daniel Denecke', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928072'}
|
Indigenous communities have led scientific innovation by providing knowledge on medicinal plants, environmental impacts on health, and sustainable agriculture. Despite these important contributions that have been transformative to society, Indigenous scientists are under-represented in scientific research. In the US, Native Americans account for only 0.24% of master and doctoral students in the science, technology, engineering, and math fields even though Indigenous people make up 2.9% of the population. Of these Indigenous graduate students, only 25% will go on to complete their graduate degree. Several studies on the success of Native Graduate students have identified the critical factors for completion of a degree as mentorship, connection to community, and an emphasis on situatedness―the ability to connect self with environment, society, and culture. A major obstacle in the implementation of success-supporting factors is the lack of systemic infrastructure and studied interventions. This National Science Foundation Innovations of Graduate Education (IGE) Track 2 award supports the Center for Indigenous Research to Create Learning and Excellence (CIRCLE) at the University of Wisconsin-Madison. CIRCLE’s goal is to increase the number of Native American students who complete graduate degrees in STEM fields by developing, implementing, and studying a model of Indigenous science support. <br/><br/>The development of CIRCLE has been led by Indigenous scientists and educators with a focus on Indigenous values of community, interdisciplinary approaches, and a strong sense of purpose. CIRCLE will focus first on mentorship training to create an environment that supports Indigenous graduate student development providing tools for conflict resolution and situatedness. The second focus of CIRCLE will be on developing a rigorous scientific community, that brings together Indigenous researchers and Tribal communities from different disciplines to cultivate innovation. Globally, the implementation of CIRCLE will provide a holistic approach for graduate student support that can be applied to all scientific training. A secondary impact of CIRCLE will be increasing the number of Indigenous scientists who will tackle challenges faced by Indigenous communities including the higher rates of exposure to environmental contaminants, metabolic disease, poverty, and a decreased lifespan of 20 years compared to the general population.<br/><br/>The Innovations in Graduate Education (IGE) program is focused on research in graduate education. The goals of IGE are to pilot, test and validate innovative approaches to graduate education and to generate the knowledge required to move these approaches into the broader community.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/05/2024
|
08/05/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2429717
|
{'FirstName': 'Judith', 'LastName': 'Simcox', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Judith Simcox', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A03NV', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Wisconsin-Madison', 'CityName': 'MADISON', 'ZipCode': '537151218', 'PhoneNumber': '6082623822', 'StreetAddress': '21 N PARK ST STE 6301', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Wisconsin', 'StateCode': 'WI', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'WI02', 'ORG_UEI_NUM': 'LCLSJAGTNZQ7', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF WISCONSIN SYSTEM', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Wisconsin-Madison', 'CityName': 'MADISON', 'StateCode': 'WI', 'ZipCode': '537151218', 'StreetAddress': '21 N PARK ST STE 6301', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Wisconsin', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'WI02'}
|
{'Code': '260Y00', 'Text': 'Innovations in Grad Education'}
|
2024~999864
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2429717.xml'}
|
IGE: Track 2: EDU EPSCoR DCL: EMPOWERS: Elevating Mentoring Practices for Optimal Work-life balance in Education and Research in STEM Graduate Studies
|
NSF
|
10/01/2024
|
09/30/2028
| 1,000,000 | 1,000,000 |
{'Value': 'Standard Grant'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Daniel Denecke', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928072'}
|
The EMPOWERS (Evaluating Mentoring Practices for Optimal Work-life balance in Education and Research in STEM graduate studies) program is an innovative, four-year, multi-dimensional approach that aims to enhance the holistic mentoring environment for faculty and graduate students. EMPOWERS was developed to respond to the emerging crisis in graduate education, which is a result of ineffective mentoring, high levels of distress in graduate students, a lack of inclusion, and a lack of career and professional development. In fact, the majority of faculty are not developed or trained in how to be an effective mentor during their graduate studies; this often becomes on-the-job training in academic positions. While effective mentoring can yield many positive benefits for the graduate student and faculty member, ineffective mentoring can lead to high rates of attrition for faculty and students, mental health concerns, and reduced well-being. This National Science Foundation Innovations in Graduate Education (IGE) Track 2 award to the Clemson University EMPOWERS program will address these issues through two innovative and distinct goals: 1) Promote holistic mentorship, which will include mentorship training, mental health and wellness, inclusion, and career and professional development; and 2) Affect systemic change at the department, college, and University levels through capacity building and policy development related to holistic mentoring. Ultimately, these two goals will lead to advances in the knowledge of effective mentoring practices while employing holistic mentor training at the university level.<br/><br/>Grounded in Ecological Systems Theory and the Cultural Framework for Institutional Change, EMPOWERS provides a novel approach to this problem by providing holistic mentor training to both graduate students and faculty members. This holistic mentor training will build upon existing curricula to address mental health, well-being, inclusion, career, and professional development, while developing mentoring plans for graduate students. Development of additional curricula will include an emphasis on responsible and ethical research conduct. The project will also determine graduate student and faculty perspectives on needed policy changes related to holistic mentoring, and how to best implement these changes at the department, college, or University levels through qualitative interviews and focus groups as well as quantitative surveys. This work will lead to the development of broad university policy changes to embed mentoring systemically, both at the graduate student and faculty levels. EMPOWERS team members from the Engineering and Science Education Department and the Graduate School will use the data from this study to build a national model of holistic mentoring.<br/><br/>The Innovations in Graduate Education (IGE) program is focused on research in graduate education. The goals of IGE are to pilot, test and validate innovative approaches to graduate education and to generate the knowledge required to move these approaches into the broader community.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/05/2024
|
08/05/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2429719
|
[{'FirstName': 'Karen', 'LastName': 'High', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Karen A High', 'EmailAddress': '[email protected]', 'NSF_ID': '000321883', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Marieke', 'LastName': 'Puymbroeck', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Marieke Puymbroeck', 'EmailAddress': '[email protected]', 'NSF_ID': '000710323', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Clemson University', 'CityName': 'CLEMSON', 'ZipCode': '296340001', 'PhoneNumber': '8646562424', 'StreetAddress': '201 SIKES HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'South Carolina', 'StateCode': 'SC', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'SC03', 'ORG_UEI_NUM': 'H2BMNX7DSKU8', 'ORG_LGL_BUS_NAME': 'CLEMSON UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Clemson University', 'CityName': 'CLEMSON', 'StateCode': 'SC', 'ZipCode': '296340001', 'StreetAddress': '201 SIKES HALL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'South Carolina', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'SC03'}
|
{'Code': '260Y00', 'Text': 'Innovations in Grad Education'}
|
2024~1000000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2429719.xml'}
|
Conference: 2024 In Vivo Ultrasound Imaging Gordon Research Conference and Seminar
|
NSF
|
06/01/2024
|
11/30/2024
| 4,990 | 4,990 |
{'Value': 'Standard Grant'}
|
{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}
|
{'SignBlockName': 'Stephanie George', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927825'}
|
This award supports the 2024 In Vivo Ultrasound Imaging Gordon Research Conference and Seminar, which will be held August 24 -30, 2024, at Waterville Valley, a Conference Center located in Waterville Valley Resort, West Dover, VT. The theme of the Conference is “Advances in Translational Applications of Imaging in Disease Diagnosis, Staging and Therapy.” Ultrasound is a ubiquitous clinical imaging modality supported by a dynamic and scholarly research community. Until the inaugural Gordon Research Conference (GRC), no conference or professional meeting was explicitly dedicated to basic science ultrasound research with the goal of improving diagnostic ultrasound. The first GRC on in vivo ultrasound imaging found an exceptional reception and outstanding feedback. Discussion among the 2022 participants quickly demonstrated the strong need to propose a Gordon Research Seminar (GRS). GRC and GRS will provide an intimate forum for scientific exchange among scientists and researchers whose primary area of research is the development of novel biomedical ultrasound techniques and approaches. The proposed inaugural GRS will feature 3 sessions with dedicated discussion leaders and 11 student speakers selected from abstract submissions. A 4-member panel discussion on mentorship will conclude the GRS and create a transition to the GRC for 5 days of fostering discourse and mentoring between trainees and researchers/educators.<br/><br/>The 2024 In Vivo Ultrasound Imaging Gordon Research Conference and Seminar is divided into two sections, the first section being in the Gordon Research Seminar (GRS) format and the second in the Gordon Research Conference format. This is the second GRC (first held in 2022) and first GRS on In Vivo Ultrasound Imaging. The GRS, which is designed for graduate students and post docs and will be held prior to the GRC, will highlight innovations and applications of next generation functional ultrasound imaging and include a mentorship session. The overall structures for both GRS and GRC sessions are the same. Sessions with three of four speakers will be managed by discussion leaders. Presentations will be followed by ample discussion time. Both sections host two poster sessions. For the GRS sessions, 3 discussion leaders and 4 panel experts have been invited and the speakers will be selected from submitted abstracts. For the GRC, 37 scientists with a focus in ultrasound research have been invited to attend as either invited speakers or discussion leaders. Topics for the 3 GRS scientific sessions are: Functional Imaging Modes, Functional Ultrasound Imaging in Therapeutic Applications, and Functional Ultrasound Neuroimaging. Topics for the 8 GRC scientific sessions are: Wearable Ultrasound Devices, Materials, and Application; Neuromodulation; Ultrasound Imaging and Therapy in Immunotherapy; Contrast Enhanced Ultrasound; Novel Uses of Contrast Agents; Lung Ultrasound; Applications of Machine Learning in Ultrasound; and Ultrasound Therapy.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
06/12/2024
|
06/12/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2429807
|
{'FirstName': 'Oliver', 'LastName': 'Kripfgans', 'PI_MID_INIT': 'D', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Oliver D Kripfgans', 'EmailAddress': '[email protected]', 'NSF_ID': '000711678', 'StartDate': '06/12/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Gordon Research Conferences', 'CityName': 'EAST GREENWICH', 'ZipCode': '028183454', 'PhoneNumber': '4017834011', 'StreetAddress': '5586 POST RD UNIT 2', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Rhode Island', 'StateCode': 'RI', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'RI02', 'ORG_UEI_NUM': 'XL5ANMKWN557', 'ORG_LGL_BUS_NAME': 'GORDON RESEARCH CONFERENCES', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Gordon Research Conferences', 'CityName': 'EAST GREENWICH', 'StateCode': 'RI', 'ZipCode': '028183454', 'StreetAddress': '5586 POST RD UNIT 2', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Rhode Island', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'RI02'}
|
{'Code': '534500', 'Text': 'Engineering of Biomed Systems'}
|
2024~4990
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2429807.xml'}
|
IGE Track 1: Integrating Artificial Intelligence Technologies into Mining Education
|
NSF
|
10/01/2024
|
09/30/2027
| 442,070 | 442,070 |
{'Value': 'Standard Grant'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Liz Webber', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924316'}
|
This National Science Foundation Innovations of Graduate Education (IGE) project at the University of Kentucky will enhance mining engineering graduate programs by integrating Artificial Intelligence (AI) knowledge and skills. The project aims to address fundamental issues such as data analytics, machine learning, and generative AI in the mining industry by creating a new course titled "Applications of Artificial Intelligence in the Mining Industry" and significantly modifying an existing course on "Mine Automation." These courses will cover critical AI applications, such as data collection, predictive analytics, safety and risk management, and ethical considerations in AI. By collaborating with leading mining companies and academic institutions, this initiative seeks to bridge the gap between AI advancements and mining education, ensuring graduates are well-equipped to tackle modern challenges in mining operations. This project will contribute to the scientific knowledge base and societal well-being by fostering innovation and promoting sustainable mining practices. <br/><br/>The hypothesis driving this project is that integrating AI-focused coursework into the mining engineering curriculum will enhance students' problem-solving abilities and adaptability to technological advancements in mining operations. The project seeks to align educational content with the practical, technological, and innovative demands of the industry, ensuring graduates are well-prepared to enter and excel in the workforce. The project's first step involves conducting a comprehensive analysis of current and emerging AI technologies impacting the mining industry through stakeholder engagement via a detailed questionnaire. This questionnaire will gather insights on AI applications, required competencies, and curriculum gaps, ensuring a diverse range of perspectives. With these insights, a flexible and comprehensive curriculum framework will be developed, covering essential AI elements from foundational concepts to advanced applications. This framework will guide the design of the syllabi for the proposed courses, balancing theoretical knowledge with practical applications. Each course will emphasize project-based learning and interdisciplinary collaboration, ensuring students gain hands-on experience with AI tools and technologies relevant to mining. A robust assessment plan will incorporate continuous feedback from academic and industry advisory boards. Semi-annual reviews will ensure the curriculum remains dynamic and responsive to technological advancements and industry needs. By aligning the educational experience with practical demands and evolving technologies, this initiative aims to prepare graduates to lead and innovate in the AI-enhanced mining sector. <br/><br/>The Innovations in Graduate Education (IGE) program is focused on research in graduate education. The goals of IGE are to pilot, test and validate innovative approaches to graduate education and to generate the knowledge required to move these approaches into the broader community.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/29/2024
|
07/29/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2429832
|
[{'FirstName': 'Steven', 'LastName': 'Schafrik', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Steven J Schafrik', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A067T', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Ali', 'LastName': 'Moradi Afrapoli', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ali Moradi Afrapoli', 'EmailAddress': '[email protected]', 'NSF_ID': '000997226', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Pedram', 'LastName': 'Roghanchi', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Pedram Roghanchi', 'EmailAddress': '[email protected]', 'NSF_ID': '000876112', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Zacharias', 'LastName': 'Agioutantis', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Zacharias Agioutantis', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A06B8', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Sarah', 'LastName': 'Wilson', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Sarah A Wilson', 'EmailAddress': '[email protected]', 'NSF_ID': '000820987', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'University of Kentucky Research Foundation', 'CityName': 'LEXINGTON', 'ZipCode': '405260001', 'PhoneNumber': '8592579420', 'StreetAddress': '500 S LIMESTONE', 'StreetAddress2': '109 KINKEAD HALL', 'CountryName': 'United States', 'StateName': 'Kentucky', 'StateCode': 'KY', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_ORG': 'KY06', 'ORG_UEI_NUM': 'H1HYA8Z1NTM5', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF KENTUCKY RESEARCH FOUNDATION, THE', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Kentucky Research Foundation', 'CityName': 'LEXINGTON', 'StateCode': 'KY', 'ZipCode': '405260001', 'StreetAddress': '500 S LIMESTONE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Kentucky', 'CountryFlag': '1', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_PERF': 'KY06'}
|
{'Code': '260Y00', 'Text': 'Innovations in Grad Education'}
|
2024~442070
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2429832.xml'}
|
Collaborative Research: ReDDDoT Phase 2: A User-Centered Platform for Digital Content Integrity
|
NSF
|
10/01/2024
|
09/30/2027
| 1,125,000 | 1,125,000 |
{'Value': 'Standard Grant'}
|
{'Code': '15020000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'ITE', 'LongName': 'Innovation and Technology Ecosystems'}}
|
{'SignBlockName': 'Danielle F. Sumy', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924217'}
|
This project seeks to protect the integrity of digital content and maintain public trust. The rapid advancement of generative Artificial Intelligence (AI) has made it easier to create and manipulate digital content, posing significant risks as high-quality deepfakes can cause major societal harm to individual people and communities. Current tools for detecting AI-generated content are fragmented and challenging to use. The project team is developing an all-in-one digital content forensics platform designed to streamline the forensic analysis process. By integrating multiple tools into a single platform, it aims to empower users by providing a reliable and user-friendly platform for detecting and mitigating the impact of deepfakes. <br/><br/>The project employs a user-centered design process, involving extensive qualitative interviews and user studies to understand needs and workflows. Based on the findings of these studies, the team is integrating various digital content forensic tools into a single platform, supported by a robust organization for the coherent navigation and selection of the tools. The team is also exploring explanation methods to enhance user comprehension of each tool’s outputs. Finally, to help users make the most of this platform, the team is creating novel game-based training scenarios and comprehensive ethical frameworks based on professional norms. The team is disseminating this work and other information about the project through workshops and professional networks in multiple user communities that will be able to leverage this platform to maintain the integrity of online digital content.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/22/2024
|
08/22/2024
|
None
|
Grant
|
47.070, 47.084
|
1
|
4900
|
4900
|
2429835
|
[{'FirstName': 'David', 'LastName': 'Schwartz', 'PI_MID_INIT': 'I', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'David I Schwartz', 'EmailAddress': '[email protected]', 'NSF_ID': '000565537', 'StartDate': '08/22/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Ersin', 'LastName': 'Uzun', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ersin Uzun', 'EmailAddress': '[email protected]', 'NSF_ID': '000595417', 'StartDate': '08/22/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Matthew', 'LastName': 'Wright', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Matthew Wright', 'EmailAddress': '[email protected]', 'NSF_ID': '000735285', 'StartDate': '08/22/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Christopher', 'LastName': 'Schwartz', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Christopher Schwartz', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A05YB', 'StartDate': '08/22/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Rochester Institute of Tech', 'CityName': 'ROCHESTER', 'ZipCode': '146235603', 'PhoneNumber': '5854757987', 'StreetAddress': '1 LOMB MEMORIAL DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '25', 'CONGRESS_DISTRICT_ORG': 'NY25', 'ORG_UEI_NUM': 'J6TWTRKC1X14', 'ORG_LGL_BUS_NAME': 'ROCHESTER INSTITUTE OF TECHNOLOGY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Rochester Institute of Tech', 'CityName': 'ROCHESTER', 'StateCode': 'NY', 'ZipCode': '146235603', 'StreetAddress': '1 LOMB MEMORIAL DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '25', 'CONGRESS_DISTRICT_PERF': 'NY25'}
|
[{'Code': '293Y00', 'Text': 'ReDDDoT-Resp Des Dev & Dp Tech'}, {'Code': '302Y00', 'Text': 'NSF-Ford Foundation Partnrshp'}]
|
2024~1125000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2429835.xml'}
|
Collaborative Research: ReDDDoT Phase 2: A User-Centered Platform for Digital Content Integrity
|
NSF
|
10/01/2024
|
09/30/2027
| 225,000 | 225,000 |
{'Value': 'Standard Grant'}
|
{'Code': '15020000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'ITE', 'LongName': 'Innovation and Technology Ecosystems'}}
|
{'SignBlockName': 'Danielle F. Sumy', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924217'}
|
This project seeks to protect the integrity of digital content and maintain public trust. The rapid advancement of generative Artificial Intelligence (AI) has made it easier to create and manipulate digital content, posing significant risks as high-quality deepfakes can cause major societal harm to individual people and communities. Current tools for detecting AI-generated content are fragmented and challenging to use. The project team is developing an all-in-one digital content forensics platform designed to streamline the forensic analysis process. By integrating multiple tools into a single platform, it aims to empower users by providing a reliable and user-friendly platform for detecting and mitigating the impact of deepfakes. <br/><br/>The project employs a user-centered design process, involving extensive qualitative interviews and user studies to understand needs and workflows. Based on the findings of these studies, the team is integrating various digital content forensic tools into a single platform, supported by a robust organization for the coherent navigation and selection of the tools. The team is also exploring explanation methods to enhance user comprehension of each tool’s outputs. Finally, to help users make the most of this platform, the team is creating novel game-based training scenarios and comprehensive ethical frameworks based on professional norms. The team is disseminating this work and other information about the project through workshops and professional networks in multiple user communities that will be able to leverage this platform to maintain the integrity of online digital content.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/22/2024
|
08/22/2024
|
None
|
Grant
|
47.084
|
1
|
4900
|
4900
|
2429836
|
{'FirstName': 'Yu', 'LastName': 'Kong', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Yu Kong', 'EmailAddress': '[email protected]', 'NSF_ID': '000789636', 'StartDate': '08/22/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Michigan State University', 'CityName': 'EAST LANSING', 'ZipCode': '488242600', 'PhoneNumber': '5173555040', 'StreetAddress': '426 AUDITORIUM RD RM 2', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Michigan', 'StateCode': 'MI', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MI07', 'ORG_UEI_NUM': 'R28EKN92ZTZ9', 'ORG_LGL_BUS_NAME': 'MICHIGAN STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'VJKZC4D1JN36'}
|
{'Name': 'Michigan State University', 'CityName': 'EAST LANSING', 'StateCode': 'MI', 'ZipCode': '488242600', 'StreetAddress': '426 AUDITORIUM RD RM 2', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Michigan', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MI07'}
|
{'Code': '293Y00', 'Text': 'ReDDDoT-Resp Des Dev & Dp Tech'}
|
2024~225000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2429836.xml'}
|
Collaborative Research: ReDDDoT Phase 2: A User-Centered Platform for Digital Content Integrity
|
NSF
|
10/01/2024
|
09/30/2027
| 150,000 | 150,000 |
{'Value': 'Standard Grant'}
|
{'Code': '15020000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'ITE', 'LongName': 'Innovation and Technology Ecosystems'}}
|
{'SignBlockName': 'Danielle F. Sumy', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924217'}
|
This project seeks to protect the integrity of digital content and maintain public trust. The rapid advancement of generative Artificial Intelligence (AI) has made it easier to create and manipulate digital content, posing significant risks as high-quality deepfakes can cause major societal harm to individual people and communities. Current tools for detecting AI-generated content are fragmented and challenging to use. The project team is developing an all-in-one digital content forensics platform designed to streamline the forensic analysis process. By integrating multiple tools into a single platform, it aims to empower users by providing a reliable and user-friendly platform for detecting and mitigating the impact of deepfakes. <br/><br/>The project employs a user-centered design process, involving extensive qualitative interviews and user studies to understand needs and workflows. Based on the findings of these studies, the team is integrating various digital content forensic tools into a single platform, supported by a robust organization for the coherent navigation and selection of the tools. The team is also exploring explanation methods to enhance user comprehension of each tool’s outputs. Finally, to help users make the most of this platform, the team is creating novel game-based training scenarios and comprehensive ethical frameworks based on professional norms. The team is disseminating this work and other information about the project through workshops and professional networks in multiple user communities that will be able to leverage this platform to maintain the integrity of online digital content.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/22/2024
|
08/22/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2429837
|
{'FirstName': 'Andrea', 'LastName': 'Hickerson', 'PI_MID_INIT': 'E', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Andrea E Hickerson', 'EmailAddress': '[email protected]', 'NSF_ID': '000831848', 'StartDate': '08/22/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Mississippi', 'CityName': 'UNIVERSITY', 'ZipCode': '386779704', 'PhoneNumber': '6629157482', 'StreetAddress': '113 FALKNER', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Mississippi', 'StateCode': 'MS', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'MS01', 'ORG_UEI_NUM': 'G1THVER8BNL4', 'ORG_LGL_BUS_NAME': 'THE UNIVERSITY OF MISSISSIPPI', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Mississippi', 'CityName': 'UNIVERSITY', 'StateCode': 'MS', 'ZipCode': '386779704', 'StreetAddress': '113 FALKNER', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Mississippi', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'MS01'}
|
{'Code': '293Y00', 'Text': 'ReDDDoT-Resp Des Dev & Dp Tech'}
|
2024~150000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2429837.xml'}
|
Scaling a Systems Approach to Inclusive Graduate Research Environments: A Track 2 Proposal to NSF's Innovations in Graduate Education (IGE) Program
|
NSF
|
10/01/2024
|
09/30/2028
| 999,699 | 999,699 |
{'Value': 'Standard Grant'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Daniel Denecke', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928072'}
|
This National Science Foundation Innovations in Graduate Education (IGE) Track 2 award to the Council of Graduate Schools (CGS) will test strategies for helping all students, and students underrepresented in graduate education in particular, to succeed in doctoral programs. Prior research at the University of California, Berkeley, has shown that underrepresented students were more likely to succeed and thrive in programs that clearly communicate expectations and rules and apply these rules consistently. Working with a network of 10 universities and 60 doctoral programs, the CGS research team will examine whether this finding holds across a broader range of institutions and program types. The research and innovations tested in this project have the potential to improve educational and career outcomes for all graduate students in three important ways. First, the project has the potential to broaden participation in the U.S. STEM workforce, improving outcomes for groups that have faced historical barriers to graduate degree completion. Second, the research and interventions tested in this project have the potential to improve the educational and career outcomes for all graduate students by creating greater transparency about the steps needed to successfully complete the PhD and transition to a STEM career. Third, the project will provide the evidence needed for universities and the NSF to invest resources in the most high-impact practices for supporting degree completion and STEM career readiness and success.<br/><br/>This project seeks to validate and scale an institutional approach to supporting equitable outcomes within STEM doctoral programs led by researchers at the University of California, Berkeley (NSF Award 1954923). That project investigated how structures operate within doctoral program research environments and found a positive relationship between a high level of program structure and positive outcomes for minoritized students as measured by student reports of psychological wellbeing and metrics of academic performance. The proposed project will test whether the findings of NSF Award 1954923 can be generalized across approximately 60 STEM graduate programs at 10 institutions. Using a mixed-method approach, the project team will 1) refine existing instruments and protocols for understanding the role of departmental structures, policies and norms on doctoral student belonging and success and adapt them to a multi-institutional study; 2) grant subawards to 10 institutions to collect data through common instruments and coordinated methods; 3) collect, clean and share benchmarking data with 10 participating institutions; 4) analyze aggregate data to understand the extent to which the positive relationship between structure and equity-related outcomes is generalizable across graduate programs in different STEM fields; 5) conduct focus groups with faculty and graduate students in doctoral programs to better understand gaps in faculty and student perceptions and experiences, based on the survey data; and 6) identify promising practices for collecting and using resulting data to support program-level and campus-wide interventions.<br/><br/>The Innovations in Graduate Education (IGE) program is focused on research in graduate education. The goals of IGE are to pilot, test and validate innovative approaches to graduate education and to generate the knowledge required to move these approaches into the broader community.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/05/2024
|
08/05/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2429880
|
[{'FirstName': 'Julia', 'LastName': 'Kent', 'PI_MID_INIT': 'D', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Julia D Kent', 'EmailAddress': '[email protected]', 'NSF_ID': '000599867', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Suzanne', 'LastName': 'Ortega', 'PI_MID_INIT': 'T', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Suzanne T Ortega', 'EmailAddress': '[email protected]', 'NSF_ID': '000676045', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Brian', 'LastName': 'McKenzie', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Brian McKenzie', 'EmailAddress': '[email protected]', 'NSF_ID': '000935275', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Council of Graduate Schools', 'CityName': 'WASHINGTON', 'ZipCode': '200361173', 'PhoneNumber': '2022233791', 'StreetAddress': '1 DUPONT CIR NW STE 230', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'District of Columbia', 'StateCode': 'DC', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_ORG': 'DC00', 'ORG_UEI_NUM': 'CU3UNKJBXGM3', 'ORG_LGL_BUS_NAME': 'COUNCIL OF GRADUATE SCHOOLS', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Council of Graduate Schools', 'CityName': 'WASHINGTON', 'StateCode': 'DC', 'ZipCode': '200361110', 'StreetAddress': '1 DUPONT CIR NW', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'District of Columbia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_PERF': 'DC00'}
|
{'Code': '260Y00', 'Text': 'Innovations in Grad Education'}
|
2024~999699
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2429880.xml'}
|
ReDDDoT Phase 2: Climate-Informed Flood Risk Mitigation Sandbox
|
NSF
|
10/01/2024
|
09/30/2027
| 1,499,722 | 1,499,722 |
{'Value': 'Standard Grant'}
|
{'Code': '15020000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'ITE', 'LongName': 'Innovation and Technology Ecosystems'}}
|
{'SignBlockName': 'Danielle F. Sumy', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924217'}
|
Floods are constantly threatening built environments and community well-being in the state of Louisiana. Floods will continue to worsen in the future with climate change. Communities must make critical decisions around flood risk mitigation and adaptation measures now. This project tackles these pressing challenges around climate change and decision-making by developing and implementing an innovative, interactive flood mitigation software application platform. The platform is designed to allow stakeholders to explore, simulate, and evaluate current and future floodplain ordinance impacts on flood risk metrics. The project will design, develop, and deploy a novel, use-inspired flood mitigation sandbox software application to support risk-informed decision-making into the future. The research team is composed of public, private, and academic partners, alongside decision-makers from five Louisiana parishes.<br/><br/>The project integrates various data sets, each contributing uniquely, and employs statistical techniques to comprehensively assess flood hazards, economic consequences, building vulnerability, and population impact. Through this project, these techniques combined will provide a holistic understanding of both current and future flood risk. The goal is to develop socially responsible and scientifically robust solutions by creating a flood mitigation sandbox tool that integrates community input with scientific research. By engaging stakeholders in the co-production and evaluation of the mitigation measures and widely disseminating project progress across sectors, the approach will foster collaboration within the scientific community and empower stakeholders to adopt evidence-based approaches, driving positive change in resilience-building efforts. The project emphasizes clear risk communication and reproducible methods, ensuring that the results are widely applicable and beneficial to low-capacity communities. This comprehensive approach will set new standards for flood risk management and community resilience, fostering collaboration and innovation across academic, industry, government, and non-profit sectors.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/20/2024
|
08/20/2024
|
None
|
Grant
|
47.050, 47.084
|
1
|
4900
|
4900
|
2429888
|
[{'FirstName': 'Carol', 'LastName': 'Friedland', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Carol J Friedland', 'EmailAddress': '[email protected]', 'NSF_ID': '000544035', 'StartDate': '08/20/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Adam', 'LastName': 'Reeder', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Adam J Reeder', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A055L', 'StartDate': '08/20/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Yao', 'LastName': 'Wang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Yao Wang', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A056S', 'StartDate': '08/20/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Md Adilur', 'LastName': 'Rahim', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Md Adilur Rahim', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A05TZ', 'StartDate': '08/20/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Rubayet Bin', 'LastName': 'Mostafiz', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Rubayet Bin Mostafiz', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A05JY', 'StartDate': '08/20/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Louisiana State University Agricultural Center', 'CityName': 'BATON ROUGE', 'ZipCode': '708030001', 'PhoneNumber': '2255786030', 'StreetAddress': '104 J NORMAN EFFERSON HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Louisiana', 'StateCode': 'LA', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_ORG': 'LA06', 'ORG_UEI_NUM': 'UF3LV6W2W6K9', 'ORG_LGL_BUS_NAME': 'LOUISIANA STATE UNIVERSITY AGRICULTURAL CENTER', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Louisiana State University Agricultural Center', 'CityName': 'BATON ROUGE', 'StateCode': 'LA', 'ZipCode': '708030001', 'StreetAddress': '104 J NORMAN EFFERSON HALL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Louisiana', 'CountryFlag': '1', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_PERF': 'LA06'}
|
[{'Code': '293Y00', 'Text': 'ReDDDoT-Resp Des Dev & Dp Tech'}, {'Code': '302Y00', 'Text': 'NSF-Ford Foundation Partnrshp'}]
|
2024~1499722
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2429888.xml'}
|
Collaborative Research: EAGER: Visual Prosody Annotation in a Sign Language Corpus
|
NSF
|
09/01/2024
|
08/31/2026
| 170,130 | 170,130 |
{'Value': 'Standard Grant'}
|
{'Code': '04040000', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'BCS', 'LongName': 'Division Of Behavioral and Cognitive Sci'}}
|
{'SignBlockName': 'Jorge Valdes Kroff', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927920'}
|
Linguists studying sign languages experience an immense resource gap. Resources for studying visual prosody in sign languages, and its grammatical and emotional functions, are scarce. This project contributes towards closing this gap and promotes data-driven sign language research. Housed in ideal research environments, the project aims to create a large sign language corpus, inclusive of dialogues, with annotations. The project plans to release this resource for linguistic and sign language technology research and provide open access teaching modules and assignments with instructor guides for use with the corpus.<br/> <br/>This project focuses on understudied characteristics in sign languages, whose study necessitates a new corpus resource, and on their reproducible annotation representations, using an iterative process of quality measurement of inter-annotator and intra-annotator agreement. The anticipated project outcomes include: (1) a sign language corpus that captures currently understudied characteristics, (2) a tested method for representing those characteristics in the corpus, (3) best practice guidelines for continued use, and (4) research dissemination in written manuscripts and video-recorded research products. Additionally, the team aims to train students and open pathways to increase the study of sign languages in the research workforce, preparing deaf scientists with linguistic research skills, and also to release a learning module for researchers. The new annotated corpus can help develop predictive models to reduce the time and resources required to carry out annotation and accelerate scientific insights, while promoting improvements to the state of the art in sign language analysis technology.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/14/2024
|
08/14/2024
|
None
|
Grant
|
47.075
|
1
|
4900
|
4900
|
2429899
|
[{'FirstName': 'Allison', 'LastName': 'Fitch', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Allison Fitch', 'EmailAddress': '[email protected]', 'NSF_ID': '000882651', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Cecilia', 'LastName': 'Alm', 'PI_MID_INIT': 'O', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Cecilia O Alm', 'EmailAddress': '[email protected]', 'NSF_ID': '000596775', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'Rochester Institute of Tech', 'CityName': 'ROCHESTER', 'ZipCode': '146235603', 'PhoneNumber': '5854757987', 'StreetAddress': '1 LOMB MEMORIAL DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '25', 'CONGRESS_DISTRICT_ORG': 'NY25', 'ORG_UEI_NUM': 'J6TWTRKC1X14', 'ORG_LGL_BUS_NAME': 'ROCHESTER INSTITUTE OF TECHNOLOGY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Rochester Institute of Tech', 'CityName': 'ROCHESTER', 'StateCode': 'NY', 'ZipCode': '146235603', 'StreetAddress': '1 LOMB MEMORIAL DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '25', 'CONGRESS_DISTRICT_PERF': 'NY25'}
|
[{'Code': '131100', 'Text': 'Linguistics'}, {'Code': '169800', 'Text': 'DS -Developmental Sciences'}]
|
2024~170130
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2429899.xml'}
|
Collaborative Research: EAGER: Visual Prosody Annotation in a Sign Language Corpus
|
NSF
|
09/01/2024
|
08/31/2026
| 129,730 | 129,730 |
{'Value': 'Standard Grant'}
|
{'Code': '04040000', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'BCS', 'LongName': 'Division Of Behavioral and Cognitive Sci'}}
|
{'SignBlockName': 'Jorge Valdes Kroff', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927920'}
|
Linguists studying sign languages experience an immense resource gap. Resources for studying visual prosody in sign languages, and its grammatical and emotional functions, are scarce. This project contributes towards closing this gap and promotes data-driven sign language research. Housed in ideal research environments, the project aims to create a large sign language corpus, inclusive of dialogues, with annotations. The project plans to release this resource for linguistic and sign language technology research and provide open access teaching modules and assignments with instructor guides for use with the corpus.<br/> <br/>This project focuses on understudied characteristics in sign languages, whose study necessitates a new corpus resource, and on their reproducible annotation representations, using an iterative process of quality measurement of inter-annotator and intra-annotator agreement. The anticipated project outcomes include: (1) a sign language corpus that captures currently understudied characteristics, (2) a tested method for representing those characteristics in the corpus, (3) best practice guidelines for continued use, and (4) research dissemination in written manuscripts and video-recorded research products. Additionally, the team aims to train students and open pathways to increase the study of sign languages in the research workforce, preparing deaf scientists with linguistic research skills, and also to release a learning module for researchers. The new annotated corpus can help develop predictive models to reduce the time and resources required to carry out annotation and accelerate scientific insights, while promoting improvements to the state of the art in sign language analysis technology.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/14/2024
|
08/14/2024
|
None
|
Grant
|
47.075
|
1
|
4900
|
4900
|
2429900
|
{'FirstName': 'Raja', 'LastName': 'Kushalnagar', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Raja Kushalnagar', 'EmailAddress': '[email protected]', 'NSF_ID': '000591743', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Gallaudet University', 'CityName': 'WASHINGTON', 'ZipCode': '200023600', 'PhoneNumber': '2026515497', 'StreetAddress': '800 FLORIDA AVE NE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'District of Columbia', 'StateCode': 'DC', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_ORG': 'DC00', 'ORG_UEI_NUM': 'TQCJUED1WEF9', 'ORG_LGL_BUS_NAME': 'GALLAUDET UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Gallaudet University', 'CityName': 'WASHINGTON', 'StateCode': 'DC', 'ZipCode': '200023600', 'StreetAddress': '800 FLORIDA AVE NE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'District of Columbia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_PERF': 'DC00'}
|
[{'Code': '131100', 'Text': 'Linguistics'}, {'Code': '169800', 'Text': 'DS -Developmental Sciences'}]
|
2024~129730
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2429900.xml'}
|
STS: Informing Klamath River Restoration Planning with Indigenous spatial analysis and community-identified relational values: Pêeshkeesh Yáv Umúsaheesh
|
NSF
|
02/01/2024
|
08/31/2025
| 504,991 | 412,893 |
{'Value': 'Standard Grant'}
|
{'Code': '04050000', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'SES', 'LongName': 'Divn Of Social and Economic Sciences'}}
|
{'SignBlockName': 'Christine Leuenberger', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927563'}
|
This project generates new ways of remixing Western and Indigenous knowledge systems to support Tribal sovereignty in river management and informs protocols for building and sharing knowledge to guide river restoration practice. The team--comprising Karuk cultural practitioners, Karuk Tribal agency staff, and non-Karuk academic researchers--will design, participate in, and evaluate an intervention into river governance to develop a plan to restore the river. The team will also interview Native and non-Native natural resource scientists to investigate how Karuk-led and Western-science-led approaches to riverscape planning. The study will be attentive to the differing ways of knowing and decision-making and how they interact with each other. Findings will be presented in a public forums and workshops as well as K-12 curriculum materials. The research will inform pressing debates about who should guide, fund, and benefit from ongoing Klamath River restoration once dam removal is complete and be of interest to policy makers, educators, citizens, and researchers. <br/><br/>This project will weave together science and technology studies (STS), critical physical geography (CPG), and Indigenous studies to contribute to reparative approaches for Indigenous-led and place-based river restoration theory and practice. By mapping field research projects with intergenerational knowledge exchanges between Native youth and elders and interviews with Native and non-Native natural resource scientists the project will investigate how Karuk-led and Western-science-led approaches to riverscape planning may conflict with and complement each other due to differing epistemologies and governance structures. It will focus on Karuk knowledge-making practices that integrate geospatial, and ethnographic data with place-based understandings of ecological processes. The team--comprising Karuk cultural practitioners, Karuk Tribal agency staff, and non Karuk academic researchers--will design, participate in, and evaluate an intervention into river governance to develop a riverscape restoration plan. The work will culminate in public presentations of findings and analysis of broader river governance processes that implement and maintain a community focused restoration plan. <br/><br/>Co-funding for this award is being provided by Navigating the New Arctic (NNA) program one of NSF's 10 Big Ideas. NNA supports projects that address convergence scientific challenges in the rapidly changing Arctic, empower new research partnerships, diversify the next generation of Arctic researchers, enhance efforts in formal and informal education, and integrate the co-production of knowledge where appropriate. This award aligns with those goals.<br/><br/>Additional co-funding of this award is provided by EcoSystem Science, Geomorphology and Land Use Dynamics, Hydrological Sciences Program and Science of Broadening Participation.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/22/2024
|
07/22/2024
|
None
|
Grant
|
47.050, 47.074, 47.075
|
1
|
4900
|
4900
|
2429912
|
{'FirstName': 'Cleo', 'LastName': 'Woelfle-Hazard', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Cleo Woelfle-Hazard', 'EmailAddress': '[email protected]', 'NSF_ID': '000732168', 'StartDate': '07/22/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of California Div of Agriculture & Natural Resources', 'CityName': 'OAKLAND', 'ZipCode': '946075201', 'PhoneNumber': '5307501306', 'StreetAddress': '1111 FRANKLIN ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'CA12', 'ORG_UEI_NUM': 'K5KAMCPRVED6', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CALIFORNIA OFFICE OF THE PRESIDENT', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of California Div of Agriculture & Natural Resources', 'CityName': 'OAKLAND', 'StateCode': 'CA', 'ZipCode': '946075201', 'StreetAddress': '1111 FRANKLIN ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'CA12'}
|
[{'Code': '104Y00', 'Text': 'NNA-Navigating the New Arctic'}, {'Code': '110Y00', 'Text': 'SBP-Science of Broadening Part'}, {'Code': '124Y00', 'Text': 'Science & Technology Studies'}, {'Code': '157900', 'Text': 'Hydrologic Sciences'}, {'Code': '738100', 'Text': 'Ecosystem Science'}, {'Code': '745800', 'Text': 'Geomorphology & Land-use Dynam'}]
|
2022~412891
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2429912.xml'}
|
Conference: ACM SIGSPATIAL Conference 2024: Student Activities and U.S.-Based Students Support
|
NSF
|
09/01/2024
|
02/28/2025
| 25,000 | 25,000 |
{'Value': 'Standard Grant'}
|
{'Code': '05020000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'IIS', 'LongName': 'Div Of Information & Intelligent Systems'}}
|
{'SignBlockName': 'Hector Munoz-Avila', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924481'}
|
This grant will fund travel of United States-based graduate and undergraduate students to participate in the 32nd ACM SIGSPATIAL GIS 2024 Conference, which will be held in Atlanta, Georgia, from October 29 to November 01, 2024. The conference is annually organized by the Association for Computing Machinery (ACM) Special Interest Group on Spatial Information (SIGSPATIAL), which is an association for researchers, students, and professionals interested in research, development, and deployment of solutions to spatial information handling and spatial knowledge extraction problems. The conference started in 1993, has established itself as the world's premier research conference in spatial computing, spatial data, and GIS. It provides a forum for original research contributions covering all conceptual, design, and implementation aspects of GIS ranging from applications, user interfaces, and visualization to storage management and indexing issues. Besides the technical program, the conference features workshops, a student research competition, a data competition, and demos. The importance of spatial information handling continuously increases with new application domains and the availability and ubiquity of large spatial data such as maps, remote-sensing images, 3D medical atlases, and the decennial census. Businesses, industry, academia, and governmental agencies utilize spatial information to improve their daily operations, structure new strategies, and increase overall productivity and US competitiveness.<br/><br/>Spatial data and applications pose novel research challenges in a wide variety of sub-areas, including (but not limited to) spatial information acquisition, modeling, data structures, and algorithms, analysis, querying and integration, human-computer interaction and visualization, and systems and architectures. From these sub-areas, deep research questions emerge that are motivated by a broad range of applications (e.g., emergency and crisis management, environmental monitoring, global positioning and location detection, geosciences, location-based and mobile services, navigation, and route planning). ACM SIGPATIAL GIS provides a forum for this research, including presentations of accepted technical papers, poster and demo exhibition encouraging lively interaction among all participants, and presentations by leading related industry members. The participation of U.S. graduate and promising undergraduate students will result in the intellectual stimulation of young minds to pursue advanced research and development activities in an area that has a huge technical and societal impact.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
05/29/2024
|
05/29/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2429933
|
[{'FirstName': 'Li', 'LastName': 'Xiong', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Li Xiong', 'EmailAddress': '[email protected]', 'NSF_ID': '000236695', 'StartDate': '05/29/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Andreas', 'LastName': 'Zuefle', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Andreas Zuefle', 'EmailAddress': '[email protected]', 'NSF_ID': '000718920', 'StartDate': '05/29/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'Emory University', 'CityName': 'ATLANTA', 'ZipCode': '303221061', 'PhoneNumber': '4047272503', 'StreetAddress': '201 DOWMAN DR NE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Georgia', 'StateCode': 'GA', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'GA05', 'ORG_UEI_NUM': 'S352L5PJLMP8', 'ORG_LGL_BUS_NAME': 'EMORY UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Emory University', 'CityName': 'ATLANTA', 'StateCode': 'GA', 'ZipCode': '303224250', 'StreetAddress': '201 DOWMAN DR NE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Georgia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'GA05'}
|
{'Code': '736400', 'Text': 'Info Integration & Informatics'}
|
2024~25000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2429933.xml'}
|
IGE: Track 1: Science to Policy: Operationalizing Knowledge from Education to Society (SPOKES)
|
NSF
|
10/01/2024
|
09/30/2027
| 498,498 | 498,498 |
{'Value': 'Standard Grant'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Karen McNeal', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922138'}
|
The academy currently produces far more PhD graduates than can find jobs as professors. Additionally, few PhD advisors have been trained to provide mentorship for career paths that lead to destinations other than academic scholarship. This dual problem highlights the need for graduate student training programs that, as they leverage students’ research skills and technical knowledge, also prepare trainees for career paths beyond the university. One such path leads towards the policy world, a professional milieu in which there is strong demand for early-career science professionals. Additionally, given the ways that policy so often sits at a convergence of scientific issues and key regional or national challenges, many STEM graduate students have a strong interest in policy work. Currently, however, there are few avenues for students to acquire the training that would prepare them for those careers. This National Science Foundation Innovations in Graduate Education (IGE) award to the University of California, Riverside (UCR) will: (1) pilot a new version of UCR’s Science to Policy (S2P) certificate course that will incorporate a set of UCR-designed, science-policy learning modules; and (2) host a series of annual SPOKES Summits whose delegates will be policy professionals. These subject matter experts (SMEs) will collaborate with the SPOKES leadership to assess and refine the science-policy competencies that ground the certificate course’s training system. These summits will culminate in the publication of the SPOKES Framework, which will establish a national standard for science-to-policy education. Thus, in addition to enabling S2P to improve the training it offers to UCR students, the project will also facilitate the SPOKES system’s dissemination to other institutions.<br/><br/>The SPOKES Project’s pilot course will be offered annually and will train PhD students from across UCR’s STEM fields. Each cohort will be trained in a set of science-policy competencies applicable to a variety of career paths (whether in policy, industry, or scholarly research). The SPOKES Competencies include knowledge of legislative processes, policy-directed research strategies, and science communication skills that cover a range of policy-relevant genres. Those competencies will provide a framework for the development of the SPOKES learning modules, which will be incorporated into each year’s certificate course as they are developed. In parallel with these efforts, the SPOKES Project will: (1) assess the learning modules by engaging policy professionals as summit SMEs who will provide feedback on those modules’ effectiveness and relevance; (2) conduct qualitative portfolio assessments by soliciting the SMEs’ feedback on students’ written and oral work, (3) collaborate with SMEs to refine S2P’s science-policy competencies, and (4) publish those competencies, along with S2P’s training methods, as the SPOKES Framework. Through their assessments of learning modules and portfolios, the SMEs will provide the feedback that will enable the SPOKES Project to refine all aspects of its training system. The SPOKES Framework will enable science-policy programs to arm their trainees with a powerful set of tools for engaging with and addressing some of our Nation’s most pressing challenges.<br/><br/>The Innovations in Graduate Education (IGE) program is focused on research in graduate education. The goals of IGE are to pilot, test and validate innovative approaches to graduate education and to generate the knowledge required to move these approaches into the broader community.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/05/2024
|
08/05/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2429934
|
[{'FirstName': 'Richard', 'LastName': 'Edwards', 'PI_MID_INIT': 'L', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Richard L Edwards', 'EmailAddress': '[email protected]', 'NSF_ID': '000651393', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Susan', 'LastName': 'Hackwood', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Susan Hackwood', 'EmailAddress': '[email protected]', 'NSF_ID': '000863445', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Annika', 'LastName': 'Speer', 'PI_MID_INIT': 'C', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Annika C Speer', 'EmailAddress': '[email protected]', 'NSF_ID': '000876610', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Benjamin', 'LastName': 'Stewart', 'PI_MID_INIT': 'W', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Benjamin W Stewart', 'EmailAddress': '[email protected]', 'NSF_ID': '000877044', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Richard', 'LastName': 'Carpiano', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Richard M Carpiano', 'EmailAddress': '[email protected]', 'NSF_ID': '000988592', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'University of California-Riverside', 'CityName': 'RIVERSIDE', 'ZipCode': '925210001', 'PhoneNumber': '9518275535', 'StreetAddress': '200 UNIVERSTY OFC BUILDING', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '39', 'CONGRESS_DISTRICT_ORG': 'CA39', 'ORG_UEI_NUM': 'MR5QC5FCAVH5', 'ORG_LGL_BUS_NAME': 'REGENTS OF THE UNIVERSITY OF CALIFORNIA AT RIVERSIDE', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of California-Riverside', 'CityName': 'RIVERSIDE', 'StateCode': 'CA', 'ZipCode': '925210001', 'StreetAddress': '200 UNIVERSTY OFC BUILDING', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '39', 'CONGRESS_DISTRICT_PERF': 'CA39'}
|
{'Code': '260Y00', 'Text': 'Innovations in Grad Education'}
|
2024~498498
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2429934.xml'}
|
WORKSHOP: WiGRAPH - Women in Graphics Research 2024
|
NSF
|
07/01/2024
|
06/30/2025
| 49,639 | 49,639 |
{'Value': 'Standard Grant'}
|
{'Code': '05020000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'IIS', 'LongName': 'Div Of Information & Intelligent Systems'}}
|
{'SignBlockName': 'Ephraim Glinert', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924341'}
|
WiGRAPH is an ACM SIGGRAPH Community Group that aims to broaden the network of women researchers in Computer Graphics. Its mission is to increase the number of women pursuing cutting-edge research in the field by creating supportive environments where women researchers can interact with each other and seek role models, mentorship, and encouragement. WiGRAPH offers a range of opportunities, including research panels, networking spaces, and an online article series that highlights the journeys and accomplishments of inspiring women researchers. The Rising Stars program is a series of workshops designed to empower women who are finishing their PhD and about to enter the job market, providing them with resources that can help them pursue research careers in the field and achieve their goals, thereby creating a more inclusive and diverse research community that can drive innovation and progress in the field.<br/><br/>The program is designed to empower and inspire young women in Computer Graphics research. Through a series of workshops and panels, it provides practical advice on how to pick research topics, pursue research questions, and navigate the industry/academic markets. This is particularly important for women researchers, especially those from underrepresented groups, who face unique challenges and obstacles in their careers. The program includes a range of workshops covering topics such as networking, negotiation, and career development, all of which are relevant to women researchers. Participants also have the opportunity to network with each other and build relationships with potential mentors and sponsors, creating a supportive community that can help women researchers thrive. Overall, the program provides women researchers with the tools they need to succeed, whether in industry or academia.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
05/29/2024
|
05/29/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2429961
|
{'FirstName': 'Adriana', 'LastName': 'Schulz', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Adriana Schulz', 'EmailAddress': '[email protected]', 'NSF_ID': '000786155', 'StartDate': '05/29/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Washington', 'CityName': 'SEATTLE', 'ZipCode': '981951016', 'PhoneNumber': '2065434043', 'StreetAddress': '4333 BROOKLYN AVE NE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Washington', 'StateCode': 'WA', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'WA07', 'ORG_UEI_NUM': 'HD1WMN6945W6', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF WASHINGTON', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Washington', 'CityName': 'SEATTLE', 'StateCode': 'WA', 'ZipCode': '981951016', 'StreetAddress': '4333 BROOKLYN AVE NE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Washington', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'WA07'}
|
{'Code': '736700', 'Text': 'HCC-Human-Centered Computing'}
|
2024~49639
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2429961.xml'}
|
IGE: Track 1: Overcoming Geographic Isolation with Research Communities
|
NSF
|
10/01/2024
|
09/30/2027
| 436,302 | 436,302 |
{'Value': 'Standard Grant'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Kathleen Ehm', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032925032'}
|
Peer-to-peer collaboration plays a vital and multifaceted role for PhD students: it helps students acquire new research skills and improve their publication records; it creates networks that provide professional support; and it helps students develop many of the key workplace skills for jobs both inside and outside of academia. Opportunities for building such research communities are severely limited or even nonexistent at small, geographically isolated institutions, where research groups are too small and specialized to lead to such collaborations, and where distance and geography limit contact with outside research groups. This National Science Foundations Innovations of Graduate Education (IGE) award to the University of Hawai’i at Mānoa will pilot and investigate an innovative model for using designed research communities to overcome some of the professional challenges faced by mathematics PhD students at geographically isolated institutions. <br/><br/>The core idea is to form research communities for mathematics doctoral students at geographically isolated institutions via a semester-long mentored research experience and follow-up activities. This project will pilot the formation of three research communities over the course of the grant, each combining several students from the University of Hawai’i Mānoa Mathematics Ph.D. program with visiting students from other institutions. To build a lasting community, the interactions will be multidimensional: the centerpiece will be an intensive, collaborative research project, but this will be buttressed by professional development related to teaching and outreach. This project will investigate the extent to which these designed research communities can provide some of the known benefits of peer-to-peer collaboration. Specifically, the project will measure the effect of this intervention on short-term benefits (e.g., feelings of belonging, motivation) and long-term benefits (e.g., persistence, job placement rate). This model has the potential to lead to many innovative possibilities for graduate education at isolated locations.<br/><br/>The Innovations in Graduate Education (IGE) program is focused on research in graduate education. The goals of IGE are to study, pilot, test and validate innovative approaches to graduate education and to generate the knowledge required to move these approaches into the broader community.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/29/2024
|
07/29/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2429967
|
[{'FirstName': 'Daniel', 'LastName': 'Erman', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Daniel Erman', 'EmailAddress': '[email protected]', 'NSF_ID': '000542918', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Elizabeth', 'LastName': 'Gross', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Elizabeth A Gross', 'EmailAddress': '[email protected]', 'NSF_ID': '000628864', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'University of Hawaii', 'CityName': 'HONOLULU', 'ZipCode': '968222247', 'PhoneNumber': '8089567800', 'StreetAddress': '2425 CAMPUS RD SINCLAIR RM 1', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Hawaii', 'StateCode': 'HI', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'HI01', 'ORG_UEI_NUM': 'NSCKLFSSABF2', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF HAWAII', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Hawaii', 'CityName': 'HONOLULU', 'StateCode': 'HI', 'ZipCode': '968222233', 'StreetAddress': '2565 McCarthy Mall', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Hawaii', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'HI01'}
|
{'Code': '260Y00', 'Text': 'Innovations in Grad Education'}
|
2024~436302
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2429967.xml'}
|
IGE: Track 2: The California State University Wellbeing Alliance for Research Masters (CSU WARM)
|
NSF
|
10/01/2024
|
09/30/2028
| 954,032 | 954,032 |
{'Value': 'Standard Grant'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Daniel Denecke', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928072'}
|
This National Science Foundation Innovations in Graduate Education (IGE) Track 2 award creates the Wellbeing Alliance for Research Masters (WARM), a collaboration between four California State University (CSU) campuses. WARM examines how mental health and wellbeing relate to the academic success of students pursuing graduate degrees in science, technology, engineering, and mathematics (STEM). With the decline in mental health across the United States, STEM graduate programs present significant challenges that can worsen students’ mental wellbeing. As a result, many students take too long to complete their graduate programs – or don’t finish at all. WARM uses an innovative app that can track mental wellbeing daily and automatically refer students to helpful resources when a concerning decline occurs. WARM also supports groups of students on each participating CSU campus, who work with faculty from various academic fields to design and deliver interventions that support wellbeing. Some of these interventions teach the students how to better cope with their experiences; others remove unnecessary barriers to success that STEM graduate programs may present. Wellbeing practices that WARM identifies as foundational to academic success are easily shared with other campuses, facilitating their adoption elsewhere.<br/><br/>WARM is guided by three general research questions. First, how do graduate program features relate to student wellbeing, psychosocial (or non-cognitive) variables, and academic success? The project will address this by auditing program practices and relevant campus resources, correlating them with academic performance, and with wellbeing and mental health as assessed by the app and surveys administered each semester. Analyses disaggregate the results by key demographic variables (such as gender and first-generation status) and control for potential confounds. Second, how does engagement with the app impact graduate student wellbeing, psychosocial variables, and academic success? This involves pre/post analyses that examine how academic success indicators and survey responses vary after students begin using the app and how these metrics differ with the level of app utilization. Third, how do targeted interventions affect wellbeing, psychosocial variables, and student success outcomes for graduate students? The project will answer this question with randomized control trials (RCTs) that compare intervention participants with a control group of non-participants, or quasi-experimental designs that control for selection biases and other potential confounds.<br/><br/>The Innovations in Graduate Education (IGE) program is focused on research in graduate education. The goals of IGE are to pilot, test and validate innovative approaches to graduate education and to generate the knowledge required to move these approaches into the broader community.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/05/2024
|
08/05/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2429971
|
[{'FirstName': 'Matthew', 'LastName': 'Cover', 'PI_MID_INIT': 'R', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Matthew R Cover', 'EmailAddress': '[email protected]', 'NSF_ID': '000657858', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Gabriela', 'LastName': 'Chavira', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Gabriela Chavira', 'EmailAddress': '[email protected]', 'NSF_ID': '000876376', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Jessica', 'LastName': 'Morales-Chicas', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jessica Morales-Chicas', 'EmailAddress': '[email protected]', 'NSF_ID': '000800580', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Amanda', 'LastName': 'Morrison', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Amanda Morrison', 'EmailAddress': '[email protected]', 'NSF_ID': '000967649', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Harold', 'LastName': 'Stanislaw', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Harold Stanislaw', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A05T5', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'California State University-Stanislaus', 'CityName': 'TURLOCK', 'ZipCode': '953823200', 'PhoneNumber': '2096673493', 'StreetAddress': 'ONE UNIVERSITY CIRCLE', 'StreetAddress2': '112A', 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'CA05', 'ORG_UEI_NUM': 'SRT1YX7KJQL4', 'ORG_LGL_BUS_NAME': 'CALIFORNIA STATE UNIVERSITY, STANISLAUS', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'California State University-Stanislaus', 'CityName': 'TURLOCK', 'StateCode': 'CA', 'ZipCode': '953823200', 'StreetAddress': 'ONE UNIVERSITY CIRCLE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'CA05'}
|
{'Code': '260Y00', 'Text': 'Innovations in Grad Education'}
|
2024~954032
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2429971.xml'}
|
Collaborative Research: ENG-SEMICON: Integrating Magneto-ionic and Ferroelectric Control of 2D Magnets for Energy-efficient Skyrmion-based Memory
|
NSF
|
11/01/2024
|
10/31/2027
| 275,000 | 275,000 |
{'Value': 'Standard Grant'}
|
{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}
|
{'SignBlockName': 'Supriyo Bandyopadhyay', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032925392'}
|
Collaborative Research: ENG-SEMICON: Integrating Magneto-ionic and Ferroelectric Control of 2D Magnets for Energy-efficient Skyrmion-based Memory<br/><br/>Non-technical abstract:<br/>Magnetic materials are widely used in today’s society. In conventional magnetic materials, their magnetic moments prefer to line up in a parallel fashion. In certain special magnetic materials, their moments wind up into a twisting pattern named “magnetic skyrmions”, which contain topological characters. Such magnetic skyrmions are considered as potentially robust information carriers for the development of novel memory devices for data storage and computing. Hence, low-voltage control of magnetic skyrmions becomes a scientifically intriguing and technologically relevant topic. This project aims to build low-power skyrmion memory based on the studies of the effects of adjacent materials such as ionic materials and ferroelectric materials on atomically thin magnets such as two-dimensional van der Waals magnets. When a small voltage is applied to either mobilize the ions or switch the ferroelectric polarization, properties of the neighboring magnets will be altered, potentially leading to the energy efficient control of magnetic skyrmions in two-dimensional magnets. When the ionic materials and ferroelectric materials are stacked together, the synergy of these two materials may enable new types of energy-efficient skyrmion memory. Graduate, undergraduate, and high-school intern students, from all backgrounds, are trained with a rich set of expertise in two-dimensional materials preparation, thin film deposition, nanoscale device fabrication, and a variety of optical and electron-beam microscopies and spectroscopies. This project can help prepare the future workforce for the semiconductor device science and technologies in the U.S. and raise the public literacy of microelectronics by new course development and local educational activities.<br/>Technical abstract:<br/>Magnetic skyrmions are topological spin textures that have been envisioned to circumvent local defects, in contrast to domain walls that are more susceptible to defect pinning, for efficient and reliable information storage and transmission. Creation and manipulation of skyrmions in ultrathin material platforms may enable energy-efficient ultracompact spintronic devices. However, traditional magnetic thin films inevitably contain defects and structural nonuniformities, hindering the development of high-performance skyrmionic devices. In stark contrast, the emergent two-dimensional van der Waals magnets exhibit single crystallinity with minimal defects, holding unique promise for exquisite control of skyrmions towards practical devices. This project aims at achieving energy-efficient skyrmion-based memory by creating, manipulating, and annihilating skyrmions in two-dimensional van der Waals magnets using magneto-ionic and ferroelectric means. First, a magneto-ionic gate will be used to locally tailor the Dzyaloshinsky-Moriya interaction and magnetic anisotropy in magnets through ionic migration. Second, heterojunctions of ferroelectrics and two-dimensional magnets will be implemented to globally engineer the atomically thin magnets for skyrmion control through polarization-tunable Dzyaloshinsky-Moriya interaction and magnetic anisotropy. Third, the magneto-ionic and ferroelectric control will be integrated onto van der Waals magnets so that (1) the electric field effect in ionic layers can be amplified by ferroelectrics, (2) the ferroelectric coercivity can be lowered by ion-modulated domain wall nucleation, and (3) as a result, the voltage controlling efficiency of skyrmions can be largely enhanced, potentially enabling low threshold voltage switching of the skyrmion phases for non-volatile memory with ultralow energy consumption. This project will have broad impacts on the understanding of magnetic skyrmions in low-dimensional systems and the development of unconventional, energy-efficient memory devices, and will serve to prepare the workforce with expertise in energy-efficient nanoelectronic devices for the microelectronics industry in the U.S.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/31/2024
|
07/31/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2429994
|
{'FirstName': 'Cheng', 'LastName': 'Gong', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Cheng Gong', 'EmailAddress': '[email protected]', 'NSF_ID': '000820380', 'StartDate': '07/31/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Maryland, College Park', 'CityName': 'COLLEGE PARK', 'ZipCode': '207425100', 'PhoneNumber': '3014056269', 'StreetAddress': '3112 LEE BUILDING', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Maryland', 'StateCode': 'MD', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'MD04', 'ORG_UEI_NUM': 'NPU8ULVAAS23', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF MARYLAND, COLLEGE PARK', 'ORG_PRNT_UEI_NUM': 'NPU8ULVAAS23'}
|
{'Name': 'University of Maryland, College Park', 'CityName': 'COLLEGE PARK', 'StateCode': 'MD', 'ZipCode': '207425100', 'StreetAddress': '3112 LEE BUILDING', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Maryland', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'MD04'}
|
{'Code': '151700', 'Text': 'EPMD-ElectrnPhoton&MagnDevices'}
|
2024~275000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2429994.xml'}
|
Collaborative Research: ENG-SEMICON: Integrating Magneto-ionic and Ferroelectric Control of 2D Magnets for Energy-efficient Skyrmion-based Memory
|
NSF
|
11/01/2024
|
10/31/2027
| 275,000 | 275,000 |
{'Value': 'Standard Grant'}
|
{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}
|
{'SignBlockName': 'Supriyo Bandyopadhyay', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032925392'}
|
Collaborative Research: ENG-SEMICON: Integrating Magneto-ionic and Ferroelectric Control of 2D Magnets for Energy-efficient Skyrmion-based Memory<br/><br/>Non-technical abstract:<br/>Magnetic materials are widely used in today’s society. In conventional magnetic materials, their magnetic moments prefer to line up in a parallel fashion. In certain special magnetic materials, their moments wind up into a twisting pattern named “magnetic skyrmions”, which contain topological characters. Such magnetic skyrmions are considered as potentially robust information carriers for the development of novel memory devices for data storage and computing. Hence, low-voltage control of magnetic skyrmions becomes a scientifically intriguing and technologically relevant topic. This project aims to build low-power skyrmion memory based on the studies of the effects of adjacent materials such as ionic materials and ferroelectric materials on atomically thin magnets such as two-dimensional van der Waals magnets. When a small voltage is applied to either mobilize the ions or switch the ferroelectric polarization, properties of the neighboring magnets will be altered, potentially leading to the energy efficient control of magnetic skyrmions in two-dimensional magnets. When the ionic materials and ferroelectric materials are stacked together, the synergy of these two materials may enable new types of energy-efficient skyrmion memory. Graduate, undergraduate, and high-school intern students, from all backgrounds, are trained with a rich set of expertise in two-dimensional materials preparation, thin film deposition, nanoscale device fabrication, and a variety of optical and electron-beam microscopies and spectroscopies. This project can help prepare the future workforce for the semiconductor device science and technologies in the U.S. and raise the public literacy of microelectronics by new course development and local educational activities.<br/>Technical abstract:<br/>Magnetic skyrmions are topological spin textures that have been envisioned to circumvent local defects, in contrast to domain walls that are more susceptible to defect pinning, for efficient and reliable information storage and transmission. Creation and manipulation of skyrmions in ultrathin material platforms may enable energy-efficient ultracompact spintronic devices. However, traditional magnetic thin films inevitably contain defects and structural nonuniformities, hindering the development of high-performance skyrmionic devices. In stark contrast, the emergent two-dimensional van der Waals magnets exhibit single crystallinity with minimal defects, holding unique promise for exquisite control of skyrmions towards practical devices. This project aims at achieving energy-efficient skyrmion-based memory by creating, manipulating, and annihilating skyrmions in two-dimensional van der Waals magnets using magneto-ionic and ferroelectric means. First, a magneto-ionic gate will be used to locally tailor the Dzyaloshinsky-Moriya interaction and magnetic anisotropy in magnets through ionic migration. Second, heterojunctions of ferroelectrics and two-dimensional magnets will be implemented to globally engineer the atomically thin magnets for skyrmion control through polarization-tunable Dzyaloshinsky-Moriya interaction and magnetic anisotropy. Third, the magneto-ionic and ferroelectric control will be integrated onto van der Waals magnets so that (1) the electric field effect in ionic layers can be amplified by ferroelectrics, (2) the ferroelectric coercivity can be lowered by ion-modulated domain wall nucleation, and (3) as a result, the voltage controlling efficiency of skyrmions can be largely enhanced, potentially enabling low threshold voltage switching of the skyrmion phases for non-volatile memory with ultralow energy consumption. This project will have broad impacts on the understanding of magnetic skyrmions in low-dimensional systems and the development of unconventional, energy-efficient memory devices, and will serve to prepare the workforce with expertise in energy-efficient nanoelectronic devices for the microelectronics industry in the U.S.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/31/2024
|
07/31/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2429995
|
{'FirstName': 'Kai', 'LastName': 'Liu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Kai Liu', 'EmailAddress': '[email protected]', 'NSF_ID': '000227631', 'StartDate': '07/31/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Georgetown University', 'CityName': 'WASHINGTON', 'ZipCode': '200570001', 'PhoneNumber': '2026250100', 'StreetAddress': 'MAIN CAMPUS', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'District of Columbia', 'StateCode': 'DC', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_ORG': 'DC00', 'ORG_UEI_NUM': 'TF2CMKY1HMX9', 'ORG_LGL_BUS_NAME': 'GEORGETOWN UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'ZFHYYLPJW7Q1'}
|
{'Name': 'Georgetown University', 'CityName': 'WASHINGTON', 'StateCode': 'DC', 'ZipCode': '200570001', 'StreetAddress': 'MAIN CAMPUS', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'District of Columbia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_PERF': 'DC00'}
|
{'Code': '151700', 'Text': 'EPMD-ElectrnPhoton&MagnDevices'}
|
2024~275000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2429995.xml'}
|
ECCS-EPSRC: Micromechanical Elements for Photonic Reconfigurable Zero-Static-Power Modules
|
NSF
|
09/01/2024
|
08/31/2027
| 413,527 | 413,527 |
{'Value': 'Standard Grant'}
|
{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}
|
{'SignBlockName': 'Margaret Kim', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922967'}
|
This project focuses on improving silicon photonic integrated circuits (PICs), which have important applications in telecommunications, quantum information, and artificial intelligence. Current methods to adjust or tune these circuits are inefficient, especially in cryogenic environments required for many future applications. Our approach introduces a new type of energy-efficient tuning element that doesn’t require continuous adjustment, inspired by techniques used in electronic memory chips. This innovation will enable more compact and efficient circuits, overcoming significant barriers in the field. The project will also foster educational growth and diversity by involving graduate students and making the designs freely available to the scientific community. <br/><br/>In silicon photonic circuits that employ microresonators, unavoidable fabrication variations mean the resonant wavelength often needs adjustment, typically through dissipative thermal tuning. In cryogenic settings, this becomes impractical. The goal of this project is to develop a new class of switchable, digital, nonvolatile micromechanical tuning elements for photonic circuits that eliminate the need for persistent, resonator-specific tuning. This approach harnesses the bistability in micromechanical beams, achieved through geometric engineering or intrinsic film stress with controlled release, enabling predictable beam deflections for controlled phase shifts in microresonators. This digital tuning approach allows for precise and stepwise adjustment of resonant wavelengths in large-scale photonic integrated circuits, without the need for continuous active tuning. This approach could enable high component density, operational energy efficiency, and compatibility with standard foundry processes.<br/><br/>This collaborative U.S.-Swiss project is supported by the U.S. National Science Foundation (NSF) and the Engineering and Physical Sciences Research Council (EPSRC) of United Kingdom Research and Innovation (UKRI), where NSF funds the U.S. investigator and EPSRC funds the partners in the United Kingdom.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/22/2024
|
07/22/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2430000
|
[{'FirstName': 'Thomas', 'LastName': 'Murphy', 'PI_MID_INIT': 'E', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Thomas E Murphy', 'EmailAddress': '[email protected]', 'NSF_ID': '000244266', 'StartDate': '07/22/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Karen', 'LastName': 'Grutter', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Karen Grutter', 'EmailAddress': '[email protected]', 'NSF_ID': '000834420', 'StartDate': '07/22/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'University of Maryland, College Park', 'CityName': 'COLLEGE PARK', 'ZipCode': '207425100', 'PhoneNumber': '3014056269', 'StreetAddress': '3112 LEE BUILDING', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Maryland', 'StateCode': 'MD', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'MD04', 'ORG_UEI_NUM': 'NPU8ULVAAS23', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF MARYLAND, COLLEGE PARK', 'ORG_PRNT_UEI_NUM': 'NPU8ULVAAS23'}
|
{'Name': 'University of Maryland, College Park', 'CityName': 'College Park', 'StateCode': 'MD', 'ZipCode': '207421000', 'StreetAddress': '3112 LEE BLDG 7809 REGENTS DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Maryland', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'MD04'}
|
{'Code': '135Y00', 'Text': 'NSF/ENG-UKRI EPSRC Opportunity'}
|
2024~413527
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430000.xml'}
|
AF: Small: Randomness in complexity theory: Fooling, sampling, and mixing
|
NSF
|
01/01/2025
|
12/31/2027
| 600,000 | 600,000 |
{'Value': 'Standard Grant'}
|
{'Code': '05010000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CCF', 'LongName': 'Division of Computing and Communication Foundations'}}
|
{'SignBlockName': 'Karl Wimmer', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922095'}
|
Computational complexity theory studies the limits of what can be computed and how much time or other resources are required to do so. Randomness plays a key role in this theory because many algorithms that use random choices can solve problems faster and more efficiently than those that do not. In cryptography, which is based on complexity theory, randomness is used to secure data and protect privacy. The study of randomness aims to ultimately improve the performance and security of everyday technology. The objective of this project is to advance the understanding of randomness in computation, with the aim of making progress on long-standing open problems. Specific areas of investigation include pseudorandom generators, which are deterministic procedures that stretch a short random seed into a much longer sequence that "looks random," the complexity of sampling distributions, and the study of mixing of distributions over mathematical structures known as groups. The investigator will foster cross-fertilization between mathematics and computer science. He will also develop publicly-available educational material, such as a book on computational complexity, and lecture notes, surveys, slides, and videos, both at the advanced and introductory levels.<br/><br/>In more detail, the investigator will work on extensions of small-bias generators, any of which can solve central open questions about pseudorandom generators. Recent work first used invariant theory to construct generators for low-degree polynomials over large fields, in fact achieving optimal parameters. The investigator will further develop this technique, with the goal of obtaining comparable pseudorandom generators over small fields, which would solve a long-standing problem in circuit complexity. The study of computational lower bounds for sampling has seen substantial progress in the last fifteen years. The investigator will further develop this area and its applications to data structures and error-correcting codes. The investigator aims to use this angle to make progress on the dictionary problem, a fundamental open problem in data structures. The study of mixing in groups has applications in communication complexity and cryptography. A recent theme has been the study of interleaved sequences of group elements. The investigator will further study interleaved mixing. A concrete aim is to resolve whether computing interleaved products requires large communication even for communication protocols involving many parties, which has been conjectured. Another aim is to use interleaved mixing to provide new separations between deterministic and randomized communication complexity. The proposed research can have an impact on a number of different areas in theoretical computer science and mathematics. Also, the investigator will continue to do research working closely with students at all levels.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/26/2024
|
07/26/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2430026
|
{'FirstName': 'Emanuele', 'LastName': 'Viola', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Emanuele Viola', 'EmailAddress': '[email protected]', 'NSF_ID': '000508907', 'StartDate': '07/26/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Northeastern University', 'CityName': 'BOSTON', 'ZipCode': '021155005', 'PhoneNumber': '6173733004', 'StreetAddress': '360 HUNTINGTON AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MA07', 'ORG_UEI_NUM': 'HLTMVS2JZBS6', 'ORG_LGL_BUS_NAME': 'NORTHEASTERN UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Northeastern University', 'CityName': 'BOSTON', 'StateCode': 'MA', 'ZipCode': '021155005', 'StreetAddress': '360 HUNTINGTON AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MA07'}
|
{'Code': '779600', 'Text': 'Algorithmic Foundations'}
|
2024~600000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430026.xml'}
|
Travel: NSF Student Travel Grant for 2024 ACM International Conference on Multimodal Interaction (ACM ICMI)
|
NSF
|
07/01/2024
|
06/30/2025
| 12,238 | 12,238 |
{'Value': 'Standard Grant'}
|
{'Code': '05020000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'IIS', 'LongName': 'Div Of Information & Intelligent Systems'}}
|
{'SignBlockName': 'Dan Cosley', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928832'}
|
This project will support abut six doctoral students enrolled in United States' institutions to attend the 26th International Conference on Multimodal Interaction (ICMI 2024) in San Jose, Costa Rica and to participate in the ICMI 2024 Doctoral Consortium that will be held on November 4, 2024. ICMI covers a range of topics around designing, developing, and evaluating multimodal interfaces and human-centered AI that are becoming commonplace in communication technology, educational software, health-tracking apps, and accessible computing systems. Novel technologies such as multi-biometric multimodal interfaces, runtime-efficient human interaction systems, and unbiased human-in-the-loop decision-making systems also promise significant contributions to individual and national security, environmental sustainability, and equitability. The Doctoral Consortium provides PhD students with an opportunity to present their work to a group of mentors and peers from an international and diverse set of academic and industrial institutions, to receive feedback on their doctoral research plan and progress, and to build a cohort of young human-computer interaction and multimodal modeling researchers. Doctoral Consortium participants will present their work both at the Doctoral Consortium itself and at the main conference poster session; the submissions will be archived in the conference proceedings and the ACM Digital Library.<br/><br/>Adequate financial support for student travel is expected to play a major role in whether or not these students attend and participate in the conference, particularly at a time when many institutions are cutting back or eliminating funds for international conference travel for students. Students from all PhD granting institutions who are in the process of forming or carrying out a plan for their PhD research in designing and developing multimodal interfaces and artificial intelligence to enhance human-human or human-computer interaction are invited to participate; the organizers will widely advertise the availability for support to attend the doctoral consortium. Students will be selected based on their contributions to intellectual, personal, and institutional diversity at the conference.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
05/29/2024
|
05/29/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2430047
|
{'FirstName': 'Brandon', 'LastName': 'Booth', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Brandon M Booth', 'EmailAddress': '[email protected]', 'NSF_ID': '000902624', 'StartDate': '05/29/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Memphis', 'CityName': 'MEMPHIS', 'ZipCode': '381520001', 'PhoneNumber': '9016783251', 'StreetAddress': '115 JOHN WILDER TOWER', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Tennessee', 'StateCode': 'TN', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_ORG': 'TN09', 'ORG_UEI_NUM': 'F2VSMAKDH8Z7', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF MEMPHIS', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Memphis', 'CityName': 'MEMPHIS', 'StateCode': 'TN', 'ZipCode': '381520001', 'StreetAddress': '115 JOHN WILDER TOWER', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Tennessee', 'CountryFlag': '1', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_PERF': 'TN09'}
|
{'Code': '736700', 'Text': 'HCC-Human-Centered Computing'}
|
2024~12238
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430047.xml'}
|
I-Corps: Translation Potential of Spectroscopic Solutions for Soil Testing
|
NSF
|
07/01/2024
|
06/30/2025
| 50,000 | 50,000 |
{'Value': 'Standard Grant'}
|
{'Code': '15030000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'TI', 'LongName': 'Translational Impacts'}}
|
{'SignBlockName': 'Ruth Shuman', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922160'}
|
The broader impact of this I-Corps project is the development of agricultural technology for soil health management. Currently, precision farming and soil testing for soil health management is limited by “wet chemistry” laboratory testing methods that require extensive sample handling and produce chemical waste. This technology may offer commercial soil testing capabilities that use locally tailored calibration models made to service clientele from specific regions, with low labor demands and no chemical waste. The goal is to connect current soil testing services with “big data” and remote sensing in agricultural systems. The use of this technology may allow the connection between precision farming and soil testing for soil health management to meet the growing demand for improved access to soil health measurements as well as data to inform policy and management decisions.<br/><br/>This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of soil spectral libraries (n > 3000 spectra) and predictive models for quantifying agronomically important soil properties. The technology uses mid-infrared (MIR) spectroscopy and an instrument that allows a seamless interface with the world’s largest MIR spectra library. Other testing technologies are based on near-infrared (NIR) technology and rely on either local or undisclosed and unverifiable spectral libraries. In soil analyses, MIR regularly outperforms NIR because it captures fundamental vibrations with much higher resolution and provides superior measurement of soil properties. In addition, this technology can quantify multiple soil properties with a single scan, compared to traditional soil analyses that require lengthy procedures for each property of interest. In the future, the goal is to leverage both local and national spectral libraries and existing soils data from potential customers. This soil analysis tool may put more information into the hands of land managers leading to better decisions and positive ramifications for building soil health and sequestering carbon in soils.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
06/17/2024
|
06/17/2024
|
None
|
Grant
|
47.084
|
1
|
4900
|
4900
|
2430074
|
[{'FirstName': 'Jessica', 'LastName': 'Miesel', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jessica Miesel', 'EmailAddress': '[email protected]', 'NSF_ID': '000638726', 'StartDate': '06/17/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Lisa', 'LastName': 'Tiemann', 'PI_MID_INIT': 'K', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Lisa K Tiemann', 'EmailAddress': '[email protected]', 'NSF_ID': '000607723', 'StartDate': '06/17/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'Michigan State University', 'CityName': 'EAST LANSING', 'ZipCode': '488242600', 'PhoneNumber': '5173555040', 'StreetAddress': '426 AUDITORIUM RD RM 2', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Michigan', 'StateCode': 'MI', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MI07', 'ORG_UEI_NUM': 'R28EKN92ZTZ9', 'ORG_LGL_BUS_NAME': 'MICHIGAN STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'VJKZC4D1JN36'}
|
{'Name': 'Michigan State University', 'CityName': 'EAST LANSING', 'StateCode': 'MI', 'ZipCode': '488242600', 'StreetAddress': '426 AUDITORIUM RD RM 2', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Michigan', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MI07'}
|
{'Code': '802300', 'Text': 'I-Corps'}
|
2024~50000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430074.xml'}
|
Synthetic Phages for Identifying and Enumerating Strains (SPIES) of bacterial pathogens
|
NSF
|
10/01/2024
|
09/30/2027
| 479,864 | 479,864 |
{'Value': 'Standard Grant'}
|
{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}
|
{'SignBlockName': 'Aleksandr Simonian', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922191'}
|
According to the Centers for Disease Control and Prevention, foodborne pathogenic bacteria cause 1.35 million illnesses, 26,500 hospitalizations, and 420 deaths in the United States each year. To address this challenge, there is a strong demand for novel biosensing technologies that can accurately count specific bacteria from food products. Bacteriophages, the widely existing viruses that naturally infect and kill bacteria, have evolved to target specific types of bacteria. This project aims to re-engineer bacteriophages to serve as biosensors for the precise enumeration of pathogenic bacteria. Leveraging advancements in synthetic biology and paper-based sensors, the proposed research will develop Synthetic Phages for Identifying and Enumerating Strains (SPIES) of pathogenic bacteria. SPIES incorporates synthetic gene circuits into the phage genome, allowing precise control over cell breakdown and reporter gene expression levels. These elements are essential for achieving high sensitivity and specificity in targeting pathogenic strains. To expand the impact of this research, the project will integrate teaching and outreach activities focused on promoting diversity and inclusion, improving retention rates, and providing hands-on experiences for K-12 students. This project not only aims to advance scientific knowledge but also contributes to the national interest by promoting the technology advancement in a real-world context, enhancing public health and safety, and supporting educational and societal welfare.<br/><br/>Current methods for detecting and counting pathogenic bacteria, such as culture-based methods, genotyping tests, and existing phage-based sensors, encounter accuracy challenges and necessitate trained personnel, specialized laboratory equipment, and time-consuming processes. The proposed SPIES technology aims to overcome these obstacles by developing synthetic phages that can express reporter genes in direct response to specific bacteria. This will be achieved by integrating toehold riboswitches into the phage genome, enabling translational-level regulation of the reporter gene, which will be activated upon detection of mRNA molecules specific to the target bacteria. Additionally, the synthetic phage will utilize a transcriptional repressor to suppress the expression of phage genes associated with host cell lysis, thereby facilitating the quantification process. By incorporating these genetic-level regulations, the engineered phage can accurately identify pathogenic Shiga toxin-producing Escherichia coli and distinguish highly virulent serotypes, such as E. coli O157. A paper-based sensing platform will be employed to store the synthetic phages, carry out phage infection, and count the infected bacterial cells. Through the integration of these innovative strategies, the SPIES technology introduces a novel bacterium sensing paradigm. It offers rapid assay time, cost-effective sensing, high specificity, and the remarkable capacity to directly count single cells with minimal user interventions.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/02/2024
|
08/02/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2430092
|
[{'FirstName': 'Zengyi', 'LastName': 'Shao', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Zengyi Shao', 'EmailAddress': '[email protected]', 'NSF_ID': '000674585', 'StartDate': '08/02/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Meng', 'LastName': 'Lu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Meng Lu', 'EmailAddress': '[email protected]', 'NSF_ID': '000674732', 'StartDate': '08/02/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'Iowa State University', 'CityName': 'AMES', 'ZipCode': '500112103', 'PhoneNumber': '5152945225', 'StreetAddress': '1350 BEARDSHEAR HALL', 'StreetAddress2': '515 MORRILL ROAD', 'CountryName': 'United States', 'StateName': 'Iowa', 'StateCode': 'IA', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'IA04', 'ORG_UEI_NUM': 'DQDBM7FGJPC5', 'ORG_LGL_BUS_NAME': 'IOWA STATE UNIVERSITY OF SCIENCE AND TECHNOLOGY', 'ORG_PRNT_UEI_NUM': 'DQDBM7FGJPC5'}
|
{'Name': 'Iowa State University', 'CityName': 'AMES', 'StateCode': 'IA', 'ZipCode': '500112103', 'StreetAddress': '1350 BEARDSHEAR HALL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Iowa', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'IA04'}
|
{'Code': '164200', 'Text': 'Special Initiatives'}
|
2024~479864
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430092.xml'}
|
Rational points on modular curves, and the geometry of arithmetic statistics
|
NSF
|
04/15/2024
|
05/31/2026
| 210,000 | 107,115 |
{'Value': 'Continuing Grant'}
|
{'Code': '03040000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'DMS', 'LongName': 'Division Of Mathematical Sciences'}}
|
{'SignBlockName': 'Andrew Pollington', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924878'}
|
The project will explore various topics within number theory and algebraic geometry. These are ancient areas of inquiry rooted in very basic questions about solving polynomial equations and motivated by concrete applications. For example, the Greek astronomer Apollonius of Perga (240-190BC) developed his theory of conics and ellipses to facilitate the study of Astronomy. Questions about numbers and shapes still remain central to the frontier of mathematical research, and this project has a particular emphasis on using modern technical tools to study classical problems. The project includes problems accessible to undergraduates and graduate students, and includes efforts including substantial student focused conference organization (such as the Arizona Winter School).<br/><br/>Mazur's torsion and isogeny theorems are cornerstones of arithmetic geometry, and arithmetic statistics is an old field full of classical problems. In recent years both areas have enjoyed an influx of new ideas and progress, especially via ideas from the geometry of numbers, moduli spaces, algebraic topology, computational number theory, and more. In particular, this project will study Mazur's ``Program B'', higher degree torsion on elliptic curves, a generalization of the Batyrev--Manin and Malle conjectures to stacks (in a sense, an interpolation of these conjectures), and non-abelian (and infinite degree) Cohen--Lenstra heuristics (and, in the function field case, theorems). Each of these sub-projects will introduced new methods and toolkits/frameworks that are expected to be broadly useful, and suggests numerous open problems and new directions for research.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
04/24/2024
|
06/11/2024
|
None
|
Grant
|
47.049
|
1
|
4900
|
4900
|
2430098
|
{'FirstName': 'David', 'LastName': 'Zureick-Brown', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'David M Zureick-Brown', 'EmailAddress': '[email protected]', 'NSF_ID': '000577368', 'StartDate': '04/24/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Amherst College', 'CityName': 'AMHERST', 'ZipCode': '010022234', 'PhoneNumber': '4135422804', 'StreetAddress': '155 S PLEASANT ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'MA02', 'ORG_UEI_NUM': 'KDRLUT71AFM5', 'ORG_LGL_BUS_NAME': 'AMHERST COLLEGE, TRUSTEES OF', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Amherst College', 'CityName': 'AMHERST', 'StateCode': 'MA', 'ZipCode': '010022234', 'StreetAddress': '155 S PLEASANT ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'MA02'}
|
{'Code': '126400', 'Text': 'ALGEBRA,NUMBER THEORY,AND COM'}
|
['2023~37130', '2024~69985']
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430098.xml'}
|
PACSP - Tools: Restoring Grassland Bird Populations using Genomically-Informed, Full Annual Cycle, Integrated Population Models
|
NSF
|
07/01/2025
|
06/30/2030
| 916,173 | 916,173 |
{'Value': 'Standard Grant'}
|
{'Code': '08090000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'IOS', 'LongName': 'Division Of Integrative Organismal Systems'}}
|
{'SignBlockName': 'Kari Segraves', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928935'}
|
The project will build a tool for land managers that will help them conserve grassland birds. North American grasslands once spanned more than 500 million acres. Grasslands are rapidly vanishing, along with the organisms that inhabit them. Grassland birds play a critical role in ecosystem health by dispersing seeds and consuming pests that damage crops and spread disease. However, grassland birds are declining faster than any other group of birds in North America, and their loss poses a threat to these important ecosystem services. One challenge with taking conservation actions to promote the recovery of grassland birds is that they migrate between distinct geographic regions each year. These migrations make it difficult to understand the factors causing population declines. To address this challenge, the project will collect data on migratory patterns, genetic health, and reproductive output of declining grassland bird populations. These data will be used to identify conservation actions that will benefit grassland bird populations, with the goal of restoring grassland bird populations across North America. In addition to building a conservation tool, the researchers will organize workshops for land managers. The project will also provide research internships for undergraduate students through Colorado State University’s MURALS First Year Scholars Academy program.<br/><br/>Since 1970, over seventy-five percent of grassland birds have declined with some species nearing threatened and endangered status. While conservation efforts aimed at reversing population declines in grassland birds are urgently needed, such efforts are currently hindered by critical gaps in our understanding of the migratory connections and demographic vital rates of populations throughout their full annual cycle. The goal of the proposed work is to develop a user-friendly tool that will aid wildlife habitat biologists in prioritizing management actions such as grassland restoration, brush management, and prescribed grazing. Specifically, the proposed research will combine data on migratory connections, genetic variation, and demographic vital rates collected across the breeding and nonbreeding grounds of three declining grassland bird species into a genomically-informed, full annual cycle, Integrated Population Model that will allow decision makers to assess which conservation measures will best promote species recovery within their jurisdiction. Furthermore, the proposed work will evaluate the effectiveness of resulting conservation recommendations by leveraging ongoing monitoring efforts.<br/><br/>This project is jointly funded by the Divisions of Environmental Biology and Integrative Organismal Systems through the Partnership to Advance Conservation Science and Practice Program.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/19/2024
|
08/19/2024
|
None
|
Grant
|
47.074
|
1
|
4900
|
4900
|
2430150
|
[{'FirstName': 'Sheela', 'LastName': 'Turbek', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Sheela Turbek', 'EmailAddress': '[email protected]', 'NSF_ID': '000868168', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Kristen', 'LastName': 'Ruegg', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Kristen Ruegg', 'EmailAddress': '[email protected]', 'NSF_ID': '000612551', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'Colorado State University', 'CityName': 'FORT COLLINS', 'ZipCode': '805212807', 'PhoneNumber': '9704916355', 'StreetAddress': '601 S HOWES ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Colorado', 'StateCode': 'CO', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'CO02', 'ORG_UEI_NUM': 'LT9CXX8L19G1', 'ORG_LGL_BUS_NAME': 'COLORADO STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Colorado State University', 'CityName': 'FORT COLLINS', 'StateCode': 'CO', 'ZipCode': '805214593', 'StreetAddress': '200 W. Lake St.', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Colorado', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'CO02'}
|
{'Code': '727500', 'Text': 'Cross-BIO Activities'}
|
2024~916173
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430150.xml'}
|
Conservation potential of existing lawns: enhancing and replacing lawns with native plants for biodiversity and ecosystem function in urban plant communities of Chicago
|
NSF
|
10/01/2024
|
09/30/2029
| 897,744 | 897,744 |
{'Value': 'Standard Grant'}
|
{'Code': '08090000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'IOS', 'LongName': 'Division Of Integrative Organismal Systems'}}
|
{'SignBlockName': 'Melissa J Coleman', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922657'}
|
Turfgrass lawns are the largest irrigated crop in the United States by land cover. Astounding amounts of water are used in their maintenance, herbicides and pesticides deliberately reduce the diversity of plants and animals, and mowing gas consumption actively contributes to climate change. Nonetheless, lawns are pre-existing greenspaces that hold extraordinary potential for biodiversity conservation. How can these spaces be changed to better serve the natural world and people? This project proposes native plant alternatives to enhance and replace lawns and will collect data to quantify the potential benefits of making the change. Introducing native lawn alternative plantings may contribute to ecosystem services that are important in urban systems, such as supporting pollinators and other wildlife, absorbing stormwater, and cooling cities, while providing refuge for native plants of our region. This project will actively enhance turfgrass lawns in Chicago area parks, collect data on the impacts of lawn conversion and enhancement, and help train scientists for research and applied conservation careers. Lawns are landscapes that decision-makers, big and small, have the power to change, from park districts to individual homeowners. Communication about the benefits of lawn alternatives is central to this work. To this end, learning gardens supported by interpretive signage will be planted in highly visited Chicago area parks and broad communication strategies through digital and print media will demonstrate the benefits of lawn alternatives to the public. <br/><br/>This project will develop evidence-based conservation planning through paired research and conservation goals dedicated to 1) understanding ecosystem service benefits associated with different urban greenspaces to explore possibilities of lawn conversion to short native plants, and 2) determining which native species could be used in low-input enhancement of turfgrass lawns. First, the results of in situ and controlled experiments will help to untangle the relationships between biodiversity and ecosystem function in urban plant communities. Researchers will measure ecosystem service (ES) provisioning, with a focus on a) supporting native plants and pollinators, b) stormwater infiltration, c) urban cooling, and d) carbon storage. We will evaluate these ES in extant urban parks within the Chicago Park District (CPD), one of the largest municipal park managers in the United States (over 8,800 acres), and in common garden experiments with replicated plots that represent an array of potential options for lawn conversion. This project will additionally advance the understanding of community assembly theory by studying how seed traits predict species emergence and establishment in existing turfgrass systems. To study the potential use of native species for lawn enhancement, phylogenetic lineage and functional traits of seeds of native tallgrass prairie species will be used to predict their ability to establish an existing lawn in a replicated greenhouse experiment. Finally, species that establish well from the greenhouse experiment will be planted into existing lawns within the CPD to assess field establishment while enhancing existing lawns.<br/><br/>This project is jointly funded by the Divisions of Environmental Biology and Integrative Organismal Systems through the Partnership to Advance Conservation Science and Practice Program.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/19/2024
|
08/19/2024
|
None
|
Grant
|
47.074
|
1
|
4900
|
4900
|
2430161
|
[{'FirstName': 'Lauren', 'LastName': 'Umek', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Lauren Umek', 'EmailAddress': '[email protected]', 'NSF_ID': '000633501', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Rebecca', 'LastName': 'Barak', 'PI_MID_INIT': 'S', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Rebecca S Barak', 'EmailAddress': '[email protected]', 'NSF_ID': '000700800', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Elizabeth', 'LastName': 'Kozik', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Elizabeth A Kozik', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A01B2', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Rebecca', 'LastName': 'Tonietto', 'PI_MID_INIT': 'K', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Rebecca K Tonietto', 'EmailAddress': '[email protected]', 'NSF_ID': '000607542', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Chicago Horticultural Society', 'CityName': 'GLENCOE', 'ZipCode': '600221168', 'PhoneNumber': '8478355440', 'StreetAddress': '1000 LAKE COOK RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Illinois', 'StateCode': 'IL', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_ORG': 'IL10', 'ORG_UEI_NUM': 'CYVTGB56VQJ7', 'ORG_LGL_BUS_NAME': 'CHICAGO HORTICULTURAL SOCIETY', 'ORG_PRNT_UEI_NUM': 'CYVTGB56VQJ7'}
|
{'Name': 'Chicago Horticultural Society', 'CityName': 'GLENCOE', 'StateCode': 'IL', 'ZipCode': '600221168', 'StreetAddress': '1000 LAKE COOK RD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Illinois', 'CountryFlag': '1', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_PERF': 'IL10'}
|
{'Code': '727500', 'Text': 'Cross-BIO Activities'}
|
2024~897744
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430161.xml'}
|
Integrating organismal biology and biogeochemistry to develop science-informed actions to conserve stream biodiversity in a changing climate
|
NSF
|
05/01/2025
|
04/30/2029
| 1,082,076 | 1,082,076 |
{'Value': 'Standard Grant'}
|
{'Code': '08090000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'IOS', 'LongName': 'Division Of Integrative Organismal Systems'}}
|
{'SignBlockName': 'Colette St. Mary', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924332'}
|
Stream animals, in particular, require well-oxygenated environments to survive and reproduce, as they are accustomed to fast moving water. Environmental changes, such as increased temperature, flooding, and sediment pollution, can interact with bacterial activity to decrease dissolved oxygen in streams and thus, threaten stream biodiversity. The steam systems of the Appalachian U.S., appear to be suffering from these effects. This project will deploy high-frequency sensors across a forest cover gradient along Appalachian stream systems to test the overarching hypothesis that accelerating climate and land use change create low oxygen ‘hotspots’ on stream bottoms that cause local extinctions. Eastern hellbenders are a giant salamander species native to Appalachia and are highly sensitive to low oxygen. Using hellbenders as a model, the study will test whether low oxygen in stream habitats causes fathers to eat their young (filial cannibalism) at frequencies leading to population declines. Coupling sensors with new underwater video technology in innovative artificial nesting habitats, the study will link bacterial activity and oxygen to individual hellbender behaviors, cannibalism, and nesting success. Moreover, these findings will guide conservation actions, including releasing thousands of hatchlings (“head-starting”) to circumvent the population declines caused by filial cannibalism, thus preventing local extinctions, preserving genetic diversity of the species, and informing future actions to conserve declining stream biodiversity, including fishes, macroinvertebrates, and amphibians. The project will also build on a strong tradition of reaching underserved Appalachian communities through educational events, strategic engagement with community members, and recruitment of undergrads from Appalachia (often first-generation students) to serve on the integrated research and conservation action team.<br/><br/>Deoxygenation of aquatic habitats is a recognized threat of climate change, but past work has largely focused on coastal ecosystems and lakes/reservoirs, leaving its effect on stream ecosystems as a significant knowledge gap. Recent advances in high-frequency sensor technology enable real-time quantification of dissolved oxygen (DO) dynamics in surface waters. However, DO measurements are rarely made in benthic stream microhabitats utilized by sensitive taxa that likely have distinct chemical environments from surface waters. Linking DO and biogeochemistry in benthic microhabitats with hellbender behavior and reproductive outcomes will transform scientific understanding of often siloed research themes – organismal, population, and ecosystem ecology – and reveal a heretofore unrecognized impact of climate change on freshwater biodiversity. The study will also be the first in any species to mechanistically connect anthropogenic change, microhabitat DO, and parental behaviors that ultimately affect population dynamics. In doing so, the work will solve a 50 yr conservation mystery. Unlike past efforts such as captive breeding and head-starting of 2–4-year-old hellbenders, data will be used to inform evidence-based actions by a Conservation Agency to rear and release hatchlings to circumvent the bottleneck at the nest caused by filial cannibalism. This action is relatively low-cost and low-risk and its efficacy will be assessed using manual surveys, infrared video surveillance, and new genomics tools. In addition to informing hellbender and other stream taxa conservation, this research will train first generation undergraduate researchers, graduate students, and postdoctoral fellows in collaborative team science, conservation biology, biogeochemistry, and science communication with the general public.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/19/2024
|
08/19/2024
|
None
|
Grant
|
47.074
|
1
|
4900
|
4900
|
2430196
|
[{'FirstName': 'William', 'LastName': 'Hopkins', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': 'III', 'PI_FULL_NAME': 'William A Hopkins', 'EmailAddress': '[email protected]', 'NSF_ID': '000258087', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Erin', 'LastName': 'Hotchkiss', 'PI_MID_INIT': 'R', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Erin R Hotchkiss', 'EmailAddress': '[email protected]', 'NSF_ID': '000581506', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Virginia Polytechnic Institute and State University', 'CityName': 'BLACKSBURG', 'ZipCode': '240603359', 'PhoneNumber': '5402315281', 'StreetAddress': '300 TURNER ST NW', 'StreetAddress2': 'STE 4200', 'CountryName': 'United States', 'StateName': 'Virginia', 'StateCode': 'VA', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_ORG': 'VA09', 'ORG_UEI_NUM': 'QDE5UHE5XD16', 'ORG_LGL_BUS_NAME': 'VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'X6KEFGLHSJX7'}
|
{'Name': 'Virginia Polytechnic Institute and State University', 'CityName': 'BLACKSBURG', 'StateCode': 'VA', 'ZipCode': '240603359', 'StreetAddress': '300 TURNER ST NW', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Virginia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_PERF': 'VA09'}
|
{'Code': '727500', 'Text': 'Cross-BIO Activities'}
|
2024~1082076
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430196.xml'}
|
ENG-AI: EPCN: Small: Computationally Efficient Learning using Graph Neural Networks with Theoretical Guarantees
|
NSF
|
01/01/2025
|
12/31/2027
| 439,539 | 439,539 |
{'Value': 'Standard Grant'}
|
{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}
|
{'SignBlockName': 'Yih-Fang Huang', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928126'}
|
Abstract for NSF proposal #2430223, entitled “ENG-AI: EPCN: Small: Computationally Efficient Learning using Graph Neural Networks with Theoretical Guarantees,”<br/><br/>PI: Wang, Meng: Associate Professor, Rensselaer Polytechnic Institute<br/><br/>Graph neural networks (GNNs) have emerged as a powerful tool for analyzing and processing graph-structured data. They have found applications in diverse fields such as robotics, power systems, recommendation engines, and social network analysis. Despite those success, their widespread application faces significant challenges, including high computational requirements and lack of interpretability and performance guarantees.<br/>This proposal aims to lay the groundwork for overcoming those challenges, establishing theoretical foundations and developing practical algorithms to enhance the efficiency and reliability of GNNs across various engineering applications. Key objectives include systematically analyzing how graph topology and network architecture influence performance by delving into the dynamics of learning and generalization in GNNs. Most of the existing theoretical works on GNNs focus on either analyzing the expressive power of GNNs or bounding the generalization gap between training and testing or characterizing the training convergence, disregarding the joint problem of learning dynamics and generalization. This study encompasses a range of GNN architectures, from established models like graph convolutional networks (GCNs) to emerging structures such as graph transformers (GTs) and graph mixture of experts (GMoEs).<br/>A crucial aspect of this proposal is the optimization of computational and memory resources in various aspects. Techniques such as graph data aggregation reduction, network pruning, attention sparsification, and dynamic joint sparsification methods will be explored to streamline GNN operations. These efforts are complemented by the introduction of novel GMoE architecture to further enhance efficiency.<br/>This proposal will advance the development of trustworthy AI systems applicable across societal infrastructures like social networks and power grids. Moreover, by focusing on computational efficiency, the proposal contributes to the advancement of green AI, aiming to reduce economic costs and environmental impact associated with large-scale AI models. Collaboration with IBM through the RPI-IBM AI Research Collaboration expands the project's reach and ensures real-world applicability. Additionally, an integral education and outreach plan is included, spanning from K-12 education to professional training, with a particular emphasis on engaging women and minority students in AI research and application.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/01/2024
|
08/01/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2430223
|
{'FirstName': 'Meng', 'LastName': 'Wang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Meng Wang', 'EmailAddress': '[email protected]', 'NSF_ID': '000634592', 'StartDate': '08/01/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Rensselaer Polytechnic Institute', 'CityName': 'TROY', 'ZipCode': '121803590', 'PhoneNumber': '5182766000', 'StreetAddress': '110 8TH ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '20', 'CONGRESS_DISTRICT_ORG': 'NY20', 'ORG_UEI_NUM': 'U5WBFKEBLMX3', 'ORG_LGL_BUS_NAME': 'RENSSELAER POLYTECHNIC INSTITUTE', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Rensselaer Polytechnic Institute', 'CityName': 'TROY', 'StateCode': 'NY', 'ZipCode': '121803590', 'StreetAddress': '110 8TH ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '20', 'CONGRESS_DISTRICT_PERF': 'NY20'}
|
{'Code': '760700', 'Text': 'EPCN-Energy-Power-Ctrl-Netwrks'}
|
2024~439539
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430223.xml'}
|
Collaborative Research: PACSP TOOLS: EPICS: Explainable AI Driven Individual Photo-Identification and Tracking for Cost-effective Conservation Study
|
NSF
|
10/01/2024
|
09/30/2029
| 630,001 | 630,001 |
{'Value': 'Standard Grant'}
|
{'Code': '08090000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'IOS', 'LongName': 'Division Of Integrative Organismal Systems'}}
|
{'SignBlockName': 'Carolyn J. Ferguson', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922689'}
|
Marine animal tracking, at both individual and group levels, is crucial for wildlife conservation. It provides essential information and invaluable insights into population dynamics, health, risks, and vulnerability, all of which help shape conservation policies, management decisions and strategies. Traditional tracking methods face significant challenges in balancing cost and precision. They either require attaching transmitters to animals that communicate with radio receivers or satellites (high accuracy but expensive and invasive) or rely on manually produced sketches from photos of distinctive features such as scars (low accuracy and labor-intensive). The overarching goal of this project is to optimize this cost-precision trade-off by designing and delivering an artificial intelligence (AI)-driven system for individual photo-identification and tracking in conservation studies of Florida manatees, a threatened species. The system aims to streamline the creation, maintenance, query, and behavior analysis of manatees using photo-identification. This project will train several graduate students, and will advance collaboration between AI researchers and conservation scientists. <br/><br/>In order to bring transformative advancements to current conservation capabilities, emphasizing cost-effective, evidence-based conservation planning, the project will 1) develop new algorithms grounded in explainable AI to identify and track individual manatees by their distinctive features, such as scars and markers, which serve as interpretable evidence for tracking; 2) support long-range spatio-temporal tracking by representing each animal as a series of sketch images throughout their lifespan, annotated with timestamps, geographic information, and metadata on life encounters; and 3) craft a framework for region-based conservation resource planning and management that models evolving patterns in local regions, including both natural and human-caused disturbances, to assess how local animal populations react to these regional changes. The collaborative research team will also extend approaches to additional threatened or endangered marine species (sea turtles, whales, rays). This project will have a lasting impact on the research community and education sectors by highlighting critical needs and showcasing viable design ideas in both conservation and computer science, and in their nexus.<br/><br/>This project is jointly funded by the Division of Environmental Biology and Integrative Organismal Systems through the Partnership to Advance Conservation Science and Practice Program.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/06/2024
|
08/06/2024
|
None
|
Grant
|
47.074
|
1
|
4900
|
4900
|
2430224
|
[{'FirstName': 'Sarah', 'LastName': 'Milton', 'PI_MID_INIT': 'L', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Sarah L Milton', 'EmailAddress': '[email protected]', 'NSF_ID': '000174319', 'StartDate': '08/06/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Xingquan', 'LastName': 'Zhu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Xingquan Zhu', 'EmailAddress': '[email protected]', 'NSF_ID': '000292045', 'StartDate': '08/06/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Matthew', 'LastName': 'Ajemian', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Matthew Ajemian', 'EmailAddress': '[email protected]', 'NSF_ID': '000754122', 'StartDate': '08/06/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Florida Atlantic University', 'CityName': 'BOCA RATON', 'ZipCode': '334316424', 'PhoneNumber': '5612970777', 'StreetAddress': '777 GLADES RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Florida', 'StateCode': 'FL', 'CONGRESSDISTRICT': '23', 'CONGRESS_DISTRICT_ORG': 'FL23', 'ORG_UEI_NUM': 'Q266L2NDAVP1', 'ORG_LGL_BUS_NAME': 'FLORIDA ATLANTIC UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Florida Atlantic University', 'CityName': 'BOCA RATON', 'StateCode': 'FL', 'ZipCode': '334316424', 'StreetAddress': '777 GLADES RD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Florida', 'CountryFlag': '1', 'CONGRESSDISTRICT': '23', 'CONGRESS_DISTRICT_PERF': 'FL23'}
|
{'Code': '727500', 'Text': 'Cross-BIO Activities'}
|
2024~630001
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430224.xml'}
|
Collaborative Research: PACSP TOOLS: EPICS: Explainable AI Driven Individual Photo-Identification and Tracking for Cost-effective Conservation Study
|
NSF
|
10/01/2024
|
09/30/2029
| 269,740 | 269,740 |
{'Value': 'Standard Grant'}
|
{'Code': '08090000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'IOS', 'LongName': 'Division Of Integrative Organismal Systems'}}
|
{'SignBlockName': 'Carolyn J. Ferguson', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922689'}
|
Marine animal tracking, at both individual and group levels, is crucial for wildlife conservation. It provides essential information and invaluable insights into population dynamics, health, risks, and vulnerability, all of which help shape conservation policies, management decisions and strategies. Traditional tracking methods face significant challenges in balancing cost and precision. They either require attaching transmitters to animals that communicate with radio receivers or satellites (high accuracy but expensive and invasive) or rely on manually produced sketches from photos of distinctive features such as scars (low accuracy and labor-intensive). The overarching goal of this project is to optimize this cost-precision trade-off by designing and delivering an artificial intelligence (AI)-driven system for individual photo-identification and tracking in conservation studies of Florida manatees, a threatened species. The system aims to streamline the creation, maintenance, query, and behavior analysis of manatees using photo-identification. This project will train several graduate students, and will advance collaboration between AI researchers and conservation scientists. <br/><br/>In order to bring transformative advancements to current conservation capabilities, emphasizing cost-effective, evidence-based conservation planning, the project will 1) develop new algorithms grounded in explainable AI to identify and track individual manatees by their distinctive features, such as scars and markers, which serve as interpretable evidence for tracking; 2) support long-range spatio-temporal tracking by representing each animal as a series of sketch images throughout their lifespan, annotated with timestamps, geographic information, and metadata on life encounters; and 3) craft a framework for region-based conservation resource planning and management that models evolving patterns in local regions, including both natural and human-caused disturbances, to assess how local animal populations react to these regional changes. The collaborative research team will also extend approaches to additional threatened or endangered marine species (sea turtles, whales, rays). This project will have a lasting impact on the research community and education sectors by highlighting critical needs and showcasing viable design ideas in both conservation and computer science, and in their nexus.<br/><br/>This project is jointly funded by the Division of Environmental Biology and Integrative Organismal Systems through the Partnership to Advance Conservation Science and Practice Program.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/06/2024
|
08/06/2024
|
None
|
Grant
|
47.074
|
1
|
4900
|
4900
|
2430226
|
[{'FirstName': 'Hans-Peter', 'LastName': 'Plag', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Hans-Peter Plag', 'EmailAddress': '[email protected]', 'NSF_ID': '000494472', 'StartDate': '08/06/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Yi', 'LastName': 'He', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Yi He', 'EmailAddress': '[email protected]', 'NSF_ID': '000875245', 'StartDate': '08/06/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'Old Dominion University Research Foundation', 'CityName': 'NORFOLK', 'ZipCode': '235082561', 'PhoneNumber': '7576834293', 'StreetAddress': '4111 MONARCH WAY', 'StreetAddress2': 'STE 204', 'CountryName': 'United States', 'StateName': 'Virginia', 'StateCode': 'VA', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'VA03', 'ORG_UEI_NUM': 'DSLXBD7UWRV6', 'ORG_LGL_BUS_NAME': 'OLD DOMINION UNIVERSITY RESEARCH FOUNDATION', 'ORG_PRNT_UEI_NUM': 'DSLXBD7UWRV6'}
|
{'Name': 'Old Dominion University', 'CityName': 'NORFOLK', 'StateCode': 'VA', 'ZipCode': '235290001', 'StreetAddress': '5115 Hampton Blvd', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Virginia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'VA03'}
|
{'Code': '727500', 'Text': 'Cross-BIO Activities'}
|
2024~269740
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430226.xml'}
|
NSF/FDA SiR: Validation and Standardization of Melanometry as a Quantitative Tool for Clinical Evaluation of Racial Disparities in Biophotonic Devices
|
NSF
|
12/15/2023
|
09/30/2025
| 200,000 | 200,000 |
{'Value': 'Standard Grant'}
|
{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}
|
{'SignBlockName': 'Steve Zehnder', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927014'}
|
Recent studies have shown that medical devices can be less accurate for patients with darker versus lighter skin. This problem can negatively affect the ability of doctors to make correct decisions about how to treat these patients, leading to worse health outcomes for patients with darker skin. Most experts believe that the primary cause of this effect is the absorption of light by melanin in the top layer of the skin. There are wide variations in the amount of melanin in the skin among the population. Instruments called melanometers can measure variables related to the amount of melanin in the skin. Using data from melanometers may help to properly account for the effect of melanin on the accuracy of medical devices in diverse populations. This proposal will develop materials that mimic skin with different amounts of melanin and blood and measure these materials with melanometers to better understand the effects of melanin and blood on the data obtained with melanometers. This project may lead to improved methods for making sure that medical devices are safe and effective for patients of all races and skin types. Results of this project will be incorporated into courses at the University of California Irvine on identifying disparities in health outcomes to illustrate how technologies can be developed and validated in a way that is equally accurate across diverse groups of patients.<br/><br/>Ensuring robustness of biophotonic technologies across the full range of skin colors is crucial for healthcare equity in clinical environments and personal health monitoring settings. Over the past two decades, numerous studies have identified racial disparities in biophotonic devices, from cerebral oximeters to photoacoustic imagers. These discrepancies can adversely impact clinical decision making, leading to worse health outcomes for patients with darker skin. Most experts believe that the primary cause of this effect is the intense, spectrally varying absorption of epidermal melanin; the concentration of which varies considerably across the population. To determine the magnitude of impact on a device, one must accurately determine the correlation between melanin content and device outputs/accuracy. Prior studies have used subjective methods, including self-identification of race and the Fitzpatrick phototype scale to assess subject pigmentation. However, objective, quantitative, and well-standardized methods based on optical measurements may provide a more precise and effective way to isolate the impact of epidermal melanin. The PI and collaborators will pursue this goal via constructing a rigorous set of synthetic tissue-simulating phantoms and using these phantoms as calibration standards to systematically characterize commercial (non-FDA-approved/cleared) melanometers for measuring skin pigmentation. Validating the outputs of these commercial devices against a well-characterized set of tissue models that simulate both melanin content and confounding tissue factors (e.g., hemoglobin, tissue scattering) will provide a critical fundamental step forward in establishing the credibility of melanometers as regulatory science tools.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
05/08/2024
|
05/08/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2430231
|
{'FirstName': 'Robert', 'LastName': 'Wilson', 'PI_MID_INIT': 'H', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Robert H Wilson', 'EmailAddress': '[email protected]', 'NSF_ID': '000888907', 'StartDate': '05/08/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Dayton', 'CityName': 'DAYTON', 'ZipCode': '454690001', 'PhoneNumber': '9372292919', 'StreetAddress': '300 COLLEGE PARK AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Ohio', 'StateCode': 'OH', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_ORG': 'OH10', 'ORG_UEI_NUM': 'V62NC51F7YV1', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF DAYTON', 'ORG_PRNT_UEI_NUM': 'V62NC51F7YV1'}
|
{'Name': 'University of Dayton', 'CityName': 'DAYTON', 'StateCode': 'OH', 'ZipCode': '454690001', 'StreetAddress': '300 COLLEGE PARK', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Ohio', 'CountryFlag': '1', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_PERF': 'OH10'}
|
[{'Code': '164200', 'Text': 'Special Initiatives'}, {'Code': '723600', 'Text': 'BioP-Biophotonics'}]
|
2023~200000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430231.xml'}
|
Collaborative Research: Adapting disturbance management to future climate in a fire-prone ecosystem: does response of an at-risk species indicate biodiversity effects?
|
NSF
|
01/01/2025
|
12/31/2027
| 293,009 | 293,009 |
{'Value': 'Standard Grant'}
|
{'Code': '08090000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'IOS', 'LongName': 'Division Of Integrative Organismal Systems'}}
|
{'SignBlockName': 'Kari Segraves', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928935'}
|
The project will test how fire affects biodiversity in fire-prone ecosystems. Disturbance is important in maintaining species diversity in most ecosystems. Fire is a common disturbance that occurs in many systems such as longleaf pine savannas. Although research has tested the effects of fire on biodiversity, little is known about how climate change might alter these effects. For example, longer or more intense droughts might reduce population recovery after a fire. This project will test how fire frequency affects biodiversity and how climate change might modify fire effects in the future. Conservation of threatened ecosystems such as longleaf pine savannas requires the ability to predict how populations will change in the future. Longleaf pine savannas are home to many threatened plants and animals like the Venus flytrap and red-cockaded woodpecker. This project will provide recommendations for prescribed burns in longleaf pine savannas and will create a web-based tool for land managers in the southeastern U.S. that will help them make conservation plans. Additionally, the project will train graduate and undergraduate students in ecology and conservation.<br/><br/>The project will explicitly test predictions that the optimal fire management strategy for Venus flytraps will differ in a future climate. These predictions were constructed using data collected under ambient variation in climate and fire regimes, rather than extreme values of climate consistent with future climate change, or experimental manipulations of fire that disentangle correlations between historical fire frequency and current fire effects. Using demographic data on Venus flytraps collected from almost-factorial manipulations of fire frequency, drought, and warming conducted across a broad geographic area, the PIs aim to construct a climate- and fire-driven integral projection model that explicitly includes site-specific effects. We will validate the model using independently collected abundance data on fire and climate effects. The proposed work will also estimate the degree to which Venus flytraps can be used as an indicator species, where a good indicator is one that accurately predicts changes in abundance of other species in response to fire and climate, rather than simply the presence of other species or of high levels of biodiversity. Assessing the indicator potential of Venus flytraps will help conservation managers identify fire frequencies that could bolster biodiversity or abundances of species of concern. These efforts will culminate in generalizable insights underlying disturbance management in a future climate and the development of a framework for assessing the utility of indicator species.<br/><br/>This project is jointly funded by the Divisions of Environmental Biology and Integrative Organismal Systems through the Partnership to Advance Conservation Science and Practice Program.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/19/2024
|
08/19/2024
|
None
|
Grant
|
47.074
|
1
|
4900
|
4900
|
2430247
|
{'FirstName': 'Allison', 'LastName': 'Louthan', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Allison M Louthan', 'EmailAddress': '[email protected]', 'NSF_ID': '000554162', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Kansas State University', 'CityName': 'MANHATTAN', 'ZipCode': '665062504', 'PhoneNumber': '7855326804', 'StreetAddress': '1601 VATTIER STREET', 'StreetAddress2': '103 FAIRCHILD HALL', 'CountryName': 'United States', 'StateName': 'Kansas', 'StateCode': 'KS', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'KS01', 'ORG_UEI_NUM': 'CFMMM5JM7HJ9', 'ORG_LGL_BUS_NAME': 'KANSAS STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Kansas State University', 'CityName': 'MANHATTAN', 'StateCode': 'KS', 'ZipCode': '665062504', 'StreetAddress': '1601 VATTIER STREET', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Kansas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'KS01'}
|
{'Code': '727500', 'Text': 'Cross-BIO Activities'}
|
2024~293009
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430247.xml'}
|
Collaborative Research: Adapting disturbance management to future climate in a fire-prone ecosystem: does response of an at-risk species indicate biodiversity effects?
|
NSF
|
01/01/2025
|
12/31/2027
| 228,825 | 228,825 |
{'Value': 'Standard Grant'}
|
{'Code': '08090000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'IOS', 'LongName': 'Division Of Integrative Organismal Systems'}}
|
{'SignBlockName': 'Kari Segraves', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928935'}
|
The project will test how fire affects biodiversity in fire-prone ecosystems. Disturbance is important in maintaining species diversity in most ecosystems. Fire is a common disturbance that occurs in many systems such as longleaf pine savannas. Although research has tested the effects of fire on biodiversity, little is known about how climate change might alter these effects. For example, longer or more intense droughts might reduce population recovery after a fire. This project will test how fire frequency affects biodiversity and how climate change might modify fire effects in the future. Conservation of threatened ecosystems such as longleaf pine savannas requires the ability to predict how populations will change in the future. Longleaf pine savannas are home to many threatened plants and animals like the Venus flytrap and red-cockaded woodpecker. This project will provide recommendations for prescribed burns in longleaf pine savannas and will create a web-based tool for land managers in the southeastern U.S. that will help them make conservation plans. Additionally, the project will train graduate and undergraduate students in ecology and conservation.<br/><br/>The project will explicitly test predictions that the optimal fire management strategy for Venus flytraps will differ in a future climate. These predictions were constructed using data collected under ambient variation in climate and fire regimes, rather than extreme values of climate consistent with future climate change, or experimental manipulations of fire that disentangle correlations between historical fire frequency and current fire effects. Using demographic data on Venus flytraps collected from almost-factorial manipulations of fire frequency, drought, and warming conducted across a broad geographic area, the PIs aim to construct a climate- and fire-driven integral projection model that explicitly includes site-specific effects. We will validate the model using independently collected abundance data on fire and climate effects. The proposed work will also estimate the degree to which Venus flytraps can be used as an indicator species, where a good indicator is one that accurately predicts changes in abundance of other species in response to fire and climate, rather than simply the presence of other species or of high levels of biodiversity. Assessing the indicator potential of Venus flytraps will help conservation managers identify fire frequencies that could bolster biodiversity or abundances of species of concern. These efforts will culminate in generalizable insights underlying disturbance management in a future climate and the development of a framework for assessing the utility of indicator species.<br/><br/>This project is jointly funded by the Divisions of Environmental Biology and Integrative Organismal Systems through the Partnership to Advance Conservation Science and Practice Program.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/19/2024
|
08/19/2024
|
None
|
Grant
|
47.074
|
1
|
4900
|
4900
|
2430248
|
{'FirstName': 'William', 'LastName': 'Morris', 'PI_MID_INIT': 'F', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'William F Morris', 'EmailAddress': '[email protected]', 'NSF_ID': '000152475', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Duke University', 'CityName': 'DURHAM', 'ZipCode': '277054640', 'PhoneNumber': '9196843030', 'StreetAddress': '2200 W MAIN ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'North Carolina', 'StateCode': 'NC', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'NC04', 'ORG_UEI_NUM': 'TP7EK8DZV6N5', 'ORG_LGL_BUS_NAME': 'DUKE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Duke University', 'CityName': 'Durham', 'StateCode': 'NC', 'ZipCode': '277054640', 'StreetAddress': '2200 W Main Street', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'North Carolina', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'NC04'}
|
{'Code': '727500', 'Text': 'Cross-BIO Activities'}
|
2024~228825
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430248.xml'}
|
Using big data and a translational ecology approach to inform full annual cycle conservation of migratory birds in the Appalachian Mountains
|
NSF
|
01/01/2025
|
12/31/2029
| 645,270 | 645,270 |
{'Value': 'Standard Grant'}
|
{'Code': '08090000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'IOS', 'LongName': 'Division Of Integrative Organismal Systems'}}
|
{'SignBlockName': 'Colette St. Mary', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924332'}
|
---------------------------------------------------------------------------------------------------------------<br/><br/>Forest management, including restoration and protection, for the conservation of bird species has generally focused on improving habitat quality for breeding birds. Thus, these efforts have been singularly focused on breeding habitats, despite the fact that many species also migrate through and rely on critical stopover habitats along the way. Neotropical migratory birds continue to decline dramatically and implementation of a more comprehensive approach to conservation has been limited by a lack of scientific understanding of the habitat needs of birds during migration. Further, when the science is available, its usefulness to inform management is often limited by a lack of input or buy-in from the land managers and owners who will ultimately need to apply recommendations on the ground. Appalachian Mountain landscapes face numerous threats including the loss of natural fire and grazing that historically helped maintain dynamic and resilient forest landscapes. Tasked with restoring and sustaining native birds and their habitats across the Appalachian region, the Appalachian Mountains Joint Venture partnership has addressed this issue by facilitating science-based conservation. This project will address these research and implementation challenges through the use of newly available big data sources to map stopover habitat use and quantify forest structure across broad spatial extents with emerging machine learning tools. Project partners will employ a translational ecology approach that centers on collaboration between science producers and science users with frequent engagement, clear communication, a well-developed participatory process, and a decision-making framework to address complicated environmental issues. This work will enhance habitat for bird species throughout the full annual cycle in the Virginia Highlands Focal Landscape, and the research and process will ultimately transform our ability to sustain healthy bird populations throughout the Appalachian region. <br/><br/>The project will bring together the state-of-the-art technologies of active remote sensing, meteorological surveillance radar, and interpretable machine learning to transform understanding of the habitat needs of birds during migration. It will characterize the aspects of forest and landscape structure that contribute to stopover habitat use during migration, compare stopover habitat use to habitat use by breeding birds, and evaluate the spatial scales at which these different features have their strongest association. This research will answer one of the most pressing problems in bird conservation science: How and where can forest management enhance habitat suitability for bird species using the same landscapes during multiple phases of the annual cycle? This research will take a translational ecology approach, addressing these questions in the context of goals and needs of science users to effectively bridge the research-implementation gap through a collaborative process that uses advances in big data and data science to inform regional conservation planning, site-level forest management implementation and ongoing monitoring to evaluate the success of the plan. <br/><br/>This project is jointly funded by the Divisions of Environmental Biology and Integrative Organismal Systems through the Partnership to Advance Conservation Science and Practice Program.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/19/2024
|
08/19/2024
|
None
|
Grant
|
47.074
|
1
|
4900
|
4900
|
2430252
|
[{'FirstName': 'Cathlyn', 'LastName': 'Davis', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Cathlyn M Davis', 'EmailAddress': '[email protected]', 'NSF_ID': '000476041', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Matthew', 'LastName': 'Fitzpatrick', 'PI_MID_INIT': 'C', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Matthew C Fitzpatrick', 'EmailAddress': '[email protected]', 'NSF_ID': '000548450', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Emily', 'LastName': 'Cohen', 'PI_MID_INIT': 'B', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Emily B Cohen', 'EmailAddress': '[email protected]', 'NSF_ID': '000797781', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'University of Maryland Center for Environmental Sciences', 'CityName': 'CAMBRIDGE', 'ZipCode': '216133368', 'PhoneNumber': '4102212014', 'StreetAddress': '2020 HORNS POINT RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Maryland', 'StateCode': 'MD', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'MD01', 'ORG_UEI_NUM': 'JHTYTGKYWLL9', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF MARYLAND CENTER FOR ENVIRONMENTAL SCIENCE', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Maryland Center for Environmental Science', 'CityName': 'Frostburg', 'StateCode': 'MD', 'ZipCode': '215322307', 'StreetAddress': '301 Braddock Rd.', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Maryland', 'CountryFlag': '1', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_PERF': 'MD06'}
|
{'Code': '727500', 'Text': 'Cross-BIO Activities'}
|
2024~645270
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430252.xml'}
|
I-Corps: Translation Potential of a High-throughput Cell Screening Technology for Bioproducts
|
NSF
|
06/01/2024
|
08/31/2024
| 50,000 | 50,000 |
{'Value': 'Standard Grant'}
|
{'Code': '15030000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'TI', 'LongName': 'Translational Impacts'}}
|
{'SignBlockName': 'Molly Wasko', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924749'}
|
The broader impact of this I-Corps project is the development of a cell selection tool that allows scientists to engineer cells that produce higher yields of various bioproducts including pharmaceutical proteins, industrial enzymes, biofuels, and cultured meats. Higher yields of bioproducts for each batch manufactured results in lower costs, which is currently the number one problem throughout the biotechnology industry. For example, the cost of a cultured meat burger is $100, orders of magnitude higher than the traditional alternatives. The cost of a gene therapy cure is $2.2 million, which is too high for the average person to afford. By bringing this new technology to market to engineer higher yielding cells, costs will be dramatically reduced for these bioproducts, allowing growth of the biotechnology industry.<br/><br/>This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. The solution is based on the development of a high-throughput cell screening technology designed to isolate cells based on their ability to produce higher yields of a desired bioproduct. Using this technology, cells are placed into hollow microparticles that are replacements for test tubes to measure the yields that cells produce. The outer shell is composed of a synthetic, porous hydrogel called poly-ethylene-glycol (PEG) that allows for continuous solution exchange between the inner compartment and the external environment. This allows for nutrients to be rapidly replenished, enabling long-term growth and production assays that were not possible with previous microfluidic screening technologies. The microparticles can be sorted via fluorescent activated cell sorters (FACS) at a rate of 75,000 cells/colonies per hour, orders of magnitude higher than the alternatives. Cells can be released post-sort by allowing the cells to grow out of the particles or by adding chemical reagents to the particles to break down the outer shell.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
05/28/2024
|
05/28/2024
|
None
|
Grant
|
47.084
|
1
|
4900
|
4900
|
2430265
|
{'FirstName': 'Dino', 'LastName': 'Di Carlo', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Dino Di Carlo', 'EmailAddress': '[email protected]', 'NSF_ID': '000508472', 'StartDate': '05/28/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of California-Los Angeles', 'CityName': 'LOS ANGELES', 'ZipCode': '900244200', 'PhoneNumber': '3107940102', 'StreetAddress': '10889 WILSHIRE BLVD STE 700', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '36', 'CONGRESS_DISTRICT_ORG': 'CA36', 'ORG_UEI_NUM': 'RN64EPNH8JC6', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CALIFORNIA, LOS ANGELES', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of California-Los Angeles', 'CityName': 'LOS ANGELES', 'StateCode': 'CA', 'ZipCode': '900951600', 'StreetAddress': '410 Westwood Plaza', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '36', 'CONGRESS_DISTRICT_PERF': 'CA36'}
|
{'Code': '802300', 'Text': 'I-Corps'}
|
2024~50000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430265.xml'}
|
EAGER: PBI: Industry Agglomeration and Innovation-Driven Economic Growth: A Framework for Data, Metrics, and Evaluation
|
NSF
|
10/01/2024
|
09/30/2026
| 299,965 | 299,965 |
{'Value': 'Standard Grant'}
|
{'Code': '15020000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'ITE', 'LongName': 'Innovation and Technology Ecosystems'}}
|
{'SignBlockName': 'Rebecca Shearman', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927403'}
|
Place-based economic development approaches have a strong potential for revitalizing lagging regional economies. Successful strategies, however, will need to consider the decision-making of private sector entities, including firms, workers, entrepreneurs, and innovators. To complement existing work on the geography of innovation, this project aims to understand clustering patterns among firms in different industries and how proximate technology infrastructure coupled with geographic clustering can affect job growth, job quality, and social and economic opportunity in a regional economy. <br/><br/>The project will use high-quality data on establishments, employment, and payroll for almost 1,000 industries to measure industry concentration patterns in tech- and innovation-driven industries. These data will document the degree of geographic concentration in specific sectors and trends over time, providing local and regional policymakers and practitioners with an understanding of the difficulty of creating new centers of tech- and innovation-driven industry activity. These data will be augmented with information on characteristics of jobs, workers, and living wages to provide insight into the benefits of successfully creating and scaling new centers of tech activity. Overall, the project will generate nearly 75 million data points illuminating agglomeration dynamics and their evolution over time and space. This will be highly relevant to regional economic development practitioners and policymakers tasked with scaling tech-based industries over the following decades.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/17/2024
|
07/17/2024
|
None
|
Grant
|
47.084
|
1
|
4900
|
4900
|
2430272
|
[{'FirstName': 'Amy', 'LastName': 'Glasmeier', 'PI_MID_INIT': 'K', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Amy K Glasmeier', 'EmailAddress': '[email protected]', 'NSF_ID': '000676481', 'StartDate': '07/17/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Teresa', 'LastName': 'Lynch', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Teresa M Lynch', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A04Y1', 'StartDate': '07/17/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Massachusetts Institute of Technology', 'CityName': 'CAMBRIDGE', 'ZipCode': '021394301', 'PhoneNumber': '6172531000', 'StreetAddress': '77 MASSACHUSETTS AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MA07', 'ORG_UEI_NUM': 'E2NYLCDML6V1', 'ORG_LGL_BUS_NAME': 'MASSACHUSETTS INSTITUTE OF TECHNOLOGY', 'ORG_PRNT_UEI_NUM': 'E2NYLCDML6V1'}
|
{'Name': 'Massachusetts Institute of Technology', 'CityName': 'CAMBRIDGE', 'StateCode': 'MA', 'ZipCode': '021394301', 'StreetAddress': '77 MASSACHUSETTS AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MA07'}
|
{'Code': '301Y00', 'Text': 'NSF Engines - Type 2'}
|
2024~299965
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430272.xml'}
|
PACSP TOOLS: Strengthening conservation partnerships by advancing molecular and analytic tools for disrupting illegal wildlife trade
|
NSF
|
01/01/2025
|
12/31/2028
| 817,942 | 817,942 |
{'Value': 'Standard Grant'}
|
{'Code': '08090000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'IOS', 'LongName': 'Division Of Integrative Organismal Systems'}}
|
{'SignBlockName': 'Carolyn J. Ferguson', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922689'}
|
Biodiversity loss is one of three critical interlinked challenges facing humanity today, alongside climate change and pollution. Nature crime, particularly, undermines the effectiveness of activities to reduce biodiversity loss. Among these crimes, illegal wildlife trade (IWT) is egregious and a cause and consequence of biodiversity loss. This illegal activity spans all US states and territories. The proposed research will use new science-practitioner partnerships to overcome scientific knowledge failures about a) data generation and classification and b) data integration and application. The science team will use sharks, rays, and turtles as conservation examples and include expertise in molecular biology, wildlife forensics, operations research, network disruption, computer and data science, conservation criminology and human geography. This research will enhance conservation efforts both in the US and globally by increasing scientific awareness and improving the precision of knowledge about the scope and rate of loss of sharks, rays and turtles involved in the illegal wildlife trade. Findings will contribute valuable data about these species and will also be integrated with other data to better understand fundamental changes of socio-environmental systems. Additionally, the results will inform science-based strategies for disrupting illegal wildlife trade including crime prevention, restorative justice, and law enforcement measures. The science team will also engage with undergraduate students through project-based learning, support PhD dissertations, and provide specialized training for law enforcement and their partners through a 5-day tool-training workshop. Furthermore, the researchers will collaborate with diverse stakeholders by sharing information, co-designing initiatives, and offering decision-making support.<br/><br/>The research aims focus on novel species identification technologies, online market analysis, data integration, and operational strategies to address fundamental challenges hindering effective action for IWT. The goals and scope of this research include: 1) producing near real time species-level genetic identification for 185 species using unique High-Resolution Melt (HRM) profiles; 2) designing and developing new machine learning frameworks that explore various HRM ranges, utilizing advanced deep learning and transfer learning approaches using data augmentation techniques; 3) advancing the accuracy of species identification through improved analysis of HRM curve profiles; 4) conducting large-scale data collection, innovative data labeling, and automatic classification to provide data openness, high recall rate, effective IWT post classification models, and a visualization tool; 5) integrating physical and virtual crime ecosystems using spatially interoperable data from experts and non-experts; 6) addressing adversarial challenges through adaptive learning and sequence creation to improve decision-making under uncertainty; and 7) developing a model structure capable of accounting for complexity of real-world networks. This research will advance science understanding and help overcome conservation knowledge failures, thereby aiding efforts to decrease the acceleration of biodiversity loss from IWT.<br/><br/>This project is jointly funded by the Divisions of Environmental Biology and Integrative Organismal Systems through the Partnership to Advance Conservation Science and Practice Program.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/19/2024
|
08/19/2024
|
None
|
Grant
|
47.074
|
1
|
4900
|
4900
|
2430277
|
[{'FirstName': 'Diego', 'LastName': 'Cardenosa', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Diego Cardenosa', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A04B0', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Renata', 'LastName': 'Konrad', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Renata A Konrad', 'EmailAddress': '[email protected]', 'NSF_ID': '000616377', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Kyumin', 'LastName': 'Lee', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Kyumin Lee', 'EmailAddress': '[email protected]', 'NSF_ID': '000662645', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Meredith', 'LastName': 'Gore', 'PI_MID_INIT': 'L', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Meredith L Gore', 'EmailAddress': '[email protected]', 'NSF_ID': '000617272', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Worcester Polytechnic Institute', 'CityName': 'WORCESTER', 'ZipCode': '016092247', 'PhoneNumber': '5088315000', 'StreetAddress': '100 INSTITUTE RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'MA02', 'ORG_UEI_NUM': 'HJNQME41NBU4', 'ORG_LGL_BUS_NAME': 'WORCESTER POLYTECHNIC INSTITUTE', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Worcester Polytechnic Institute', 'CityName': 'WORCESTER', 'StateCode': 'MA', 'ZipCode': '016092247', 'StreetAddress': '100 INSTITUTE RD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'MA02'}
|
{'Code': '727500', 'Text': 'Cross-BIO Activities'}
|
2024~817942
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430277.xml'}
|
Collaborative Research: PACSP TOOLS:Identifying unique genotypic and phenotypic characteristics of Gulf Coast canids to revive genomic variation in the endangered red wolf
|
NSF
|
07/01/2025
|
06/30/2030
| 118,081 | 118,081 |
{'Value': 'Standard Grant'}
|
{'Code': '08090000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'IOS', 'LongName': 'Division Of Integrative Organismal Systems'}}
|
{'SignBlockName': 'Colette St. Mary', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924332'}
|
Past hybridization among closely related species can leave traces of genetic variation from endangered or even extinct species in the DNA of present-day animals. This phenomenon, known as ghost introgression, is often overlooked but is a reservoir of preserved genetic variation from endangered or extinct species found in present-day genomes of the related common species. These hidden reservoirs could be essential for conserving adaptive potential in the future. This project re-envisions the conservation value of ghost introgression and how it can be leveraged to support endangered species recovery. The project will characterize the ecology and population dynamics of Gulf Coast canids that carry varying amounts of red wolf ghost ancestry in their coyote genomes and inhabit a broad geographic range. First it will develop a non-invasive genetic tool to monitor and assess the ecological conditions that promote the persistence of red wolf ghost ancestry. Further, the tool will be used to identify individuals of high conservation value, as measured by their degree of unique red wolf ghost ancestry and thus have the greatest potential to resuscitate endangered red wolf ghost genetic variation. The conservation partner, the Endangered Wolf Center, will then implement a short-term breeding experiment to enhance ghost ancestry based on a careful pairing design in a captive breeding facility. The project integrates information and efforts across communities and organizations to pioneer new options for endangered species recovery programs in the future. The project will also involve public outreach and education, and engagement with managers with a focus on resolving human wildlife conflicts and conservation of key predators.<br/><br/>Canids along the American Gulf Coast carry signatures of red wolf ghost introgression, yet little is known about the factors that support the persistence of such. The project will combine in- and ex-situ studies and develop a framework for evidence-based conservation in a natural landscape using population ecology and empirical genomics. First, canids will be captured, genetically sampled, and radio-monitored across a gradient of mortality risk and available resources to quantify the functional linkage between ghost introgression and ecology. Morphometrics and individual-level fitness correlates will also be considered to develop a landscape prioritization tool to identify areas for future conservation efforts. Second, a SNP panel will be developed to non-invasively monitor large landscapes for ghost introgression of red wolf DNA and behavioral ecology traits. The application of this technology will be for large-scale, cost effective, long-term, non-invasive monitoring and continued identification of conservation priority individuals. Third, an optimization framework will be developed to identify and rank individuals that maximize ghost genetic variation while prioritizing the genomic architecture of red wolf ancestry, noting that longer block lengths of endangered genetics are preferred for maintaining genome integrity. Finally, the project will attempt to revive ghost variation through an innovative short-term captive breeding experiment, challenging the existing endangered species conservation tenets to include ghost variation as a trailblazing method to protect imperiled species and diversify their genomes. This project will serve as a model, evaluating the potential of leveraging ghost introgression to preserve the genomes of endangered species that face the immediate threat of extinction.<br/><br/>This project is jointly funded by the Divisions of Environmental Biology and Integrative Organismal Systems through the Partnership to Advance Conservation Science and Practice Program.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/19/2024
|
08/19/2024
|
None
|
Grant
|
47.074
|
1
|
4900
|
4900
|
2430281
|
{'FirstName': 'Bridgett', 'LastName': 'vonHoldt', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Bridgett vonHoldt', 'EmailAddress': '[email protected]', 'NSF_ID': '000625102', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Princeton University', 'CityName': 'PRINCETON', 'ZipCode': '085442001', 'PhoneNumber': '6092583090', 'StreetAddress': '1 NASSAU HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New Jersey', 'StateCode': 'NJ', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'NJ12', 'ORG_UEI_NUM': 'NJ1YPQXQG7U5', 'ORG_LGL_BUS_NAME': 'THE TRUSTEES OF PRINCETON UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Princeton University', 'CityName': 'PRINCETON', 'StateCode': 'NJ', 'ZipCode': '085442001', 'StreetAddress': '1 NASSAU HALL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New Jersey', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'NJ12'}
|
{'Code': '727500', 'Text': 'Cross-BIO Activities'}
|
2024~118081
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430281.xml'}
|
Collaborative Research: PACSP TOOLS:Identifying unique genotypic and phenotypic characteristics of Gulf Coast canids to revive genomic variation in the endangered red wolf
|
NSF
|
07/01/2025
|
06/30/2030
| 207,612 | 207,612 |
{'Value': 'Standard Grant'}
|
{'Code': '08090000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'IOS', 'LongName': 'Division Of Integrative Organismal Systems'}}
|
{'SignBlockName': 'Colette St. Mary', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924332'}
|
Past hybridization among closely related species can leave traces of genetic variation from endangered or even extinct species in the DNA of present-day animals. This phenomenon, known as ghost introgression, is often overlooked but is a reservoir of preserved genetic variation from endangered or extinct species found in present-day genomes of the related common species. These hidden reservoirs could be essential for conserving adaptive potential in the future. This project re-envisions the conservation value of ghost introgression and how it can be leveraged to support endangered species recovery. The project will characterize the ecology and population dynamics of Gulf Coast canids that carry varying amounts of red wolf ghost ancestry in their coyote genomes and inhabit a broad geographic range. First it will develop a non-invasive genetic tool to monitor and assess the ecological conditions that promote the persistence of red wolf ghost ancestry. Further, the tool will be used to identify individuals of high conservation value, as measured by their degree of unique red wolf ghost ancestry and thus have the greatest potential to resuscitate endangered red wolf ghost genetic variation. The conservation partner, the Endangered Wolf Center, will then implement a short-term breeding experiment to enhance ghost ancestry based on a careful pairing design in a captive breeding facility. The project integrates information and efforts across communities and organizations to pioneer new options for endangered species recovery programs in the future. The project will also involve public outreach and education, and engagement with managers with a focus on resolving human wildlife conflicts and conservation of key predators.<br/><br/>Canids along the American Gulf Coast carry signatures of red wolf ghost introgression, yet little is known about the factors that support the persistence of such. The project will combine in- and ex-situ studies and develop a framework for evidence-based conservation in a natural landscape using population ecology and empirical genomics. First, canids will be captured, genetically sampled, and radio-monitored across a gradient of mortality risk and available resources to quantify the functional linkage between ghost introgression and ecology. Morphometrics and individual-level fitness correlates will also be considered to develop a landscape prioritization tool to identify areas for future conservation efforts. Second, a SNP panel will be developed to non-invasively monitor large landscapes for ghost introgression of red wolf DNA and behavioral ecology traits. The application of this technology will be for large-scale, cost effective, long-term, non-invasive monitoring and continued identification of conservation priority individuals. Third, an optimization framework will be developed to identify and rank individuals that maximize ghost genetic variation while prioritizing the genomic architecture of red wolf ancestry, noting that longer block lengths of endangered genetics are preferred for maintaining genome integrity. Finally, the project will attempt to revive ghost variation through an innovative short-term captive breeding experiment, challenging the existing endangered species conservation tenets to include ghost variation as a trailblazing method to protect imperiled species and diversify their genomes. This project will serve as a model, evaluating the potential of leveraging ghost introgression to preserve the genomes of endangered species that face the immediate threat of extinction.<br/><br/>This project is jointly funded by the Divisions of Environmental Biology and Integrative Organismal Systems through the Partnership to Advance Conservation Science and Practice Program.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/19/2024
|
08/19/2024
|
None
|
Grant
|
47.074
|
1
|
4900
|
4900
|
2430282
|
{'FirstName': 'Kristin', 'LastName': 'Brzeski', 'PI_MID_INIT': 'E', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Kristin E Brzeski', 'EmailAddress': '[email protected]', 'NSF_ID': '000688689', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Michigan Technological University', 'CityName': 'HOUGHTON', 'ZipCode': '499311200', 'PhoneNumber': '9064871885', 'StreetAddress': '1400 TOWNSEND DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Michigan', 'StateCode': 'MI', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'MI01', 'ORG_UEI_NUM': 'GKMSN3DA6P91', 'ORG_LGL_BUS_NAME': 'MICHIGAN TECHNOLOGICAL UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'GKMSN3DA6P91'}
|
{'Name': 'Michigan Technological University', 'CityName': 'HOUGHTON', 'StateCode': 'MI', 'ZipCode': '499311200', 'StreetAddress': '1400 TOWNSEND DRIVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Michigan', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'MI01'}
|
{'Code': '727500', 'Text': 'Cross-BIO Activities'}
|
2024~207612
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430282.xml'}
|
Collaborative Research: PACSP TOOLS:Identifying unique genotypic and phenotypic characteristics of Gulf Coast canids to revive genomic variation in the endangered red wolf
|
NSF
|
07/01/2025
|
06/30/2030
| 251,552 | 251,552 |
{'Value': 'Standard Grant'}
|
{'Code': '08090000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'IOS', 'LongName': 'Division Of Integrative Organismal Systems'}}
|
{'SignBlockName': 'Colette St. Mary', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924332'}
|
Past hybridization among closely related species can leave traces of genetic variation from endangered or even extinct species in the DNA of present-day animals. This phenomenon, known as ghost introgression, is often overlooked but is a reservoir of preserved genetic variation from endangered or extinct species found in present-day genomes of the related common species. These hidden reservoirs could be essential for conserving adaptive potential in the future. This project re-envisions the conservation value of ghost introgression and how it can be leveraged to support endangered species recovery. The project will characterize the ecology and population dynamics of Gulf Coast canids that carry varying amounts of red wolf ghost ancestry in their coyote genomes and inhabit a broad geographic range. First it will develop a non-invasive genetic tool to monitor and assess the ecological conditions that promote the persistence of red wolf ghost ancestry. Further, the tool will be used to identify individuals of high conservation value, as measured by their degree of unique red wolf ghost ancestry and thus have the greatest potential to resuscitate endangered red wolf ghost genetic variation. The conservation partner, the Endangered Wolf Center, will then implement a short-term breeding experiment to enhance ghost ancestry based on a careful pairing design in a captive breeding facility. The project integrates information and efforts across communities and organizations to pioneer new options for endangered species recovery programs in the future. The project will also involve public outreach and education, and engagement with managers with a focus on resolving human wildlife conflicts and conservation of key predators.<br/><br/>Canids along the American Gulf Coast carry signatures of red wolf ghost introgression, yet little is known about the factors that support the persistence of such. The project will combine in- and ex-situ studies and develop a framework for evidence-based conservation in a natural landscape using population ecology and empirical genomics. First, canids will be captured, genetically sampled, and radio-monitored across a gradient of mortality risk and available resources to quantify the functional linkage between ghost introgression and ecology. Morphometrics and individual-level fitness correlates will also be considered to develop a landscape prioritization tool to identify areas for future conservation efforts. Second, a SNP panel will be developed to non-invasively monitor large landscapes for ghost introgression of red wolf DNA and behavioral ecology traits. The application of this technology will be for large-scale, cost effective, long-term, non-invasive monitoring and continued identification of conservation priority individuals. Third, an optimization framework will be developed to identify and rank individuals that maximize ghost genetic variation while prioritizing the genomic architecture of red wolf ancestry, noting that longer block lengths of endangered genetics are preferred for maintaining genome integrity. Finally, the project will attempt to revive ghost variation through an innovative short-term captive breeding experiment, challenging the existing endangered species conservation tenets to include ghost variation as a trailblazing method to protect imperiled species and diversify their genomes. This project will serve as a model, evaluating the potential of leveraging ghost introgression to preserve the genomes of endangered species that face the immediate threat of extinction.<br/><br/>This project is jointly funded by the Divisions of Environmental Biology and Integrative Organismal Systems through the Partnership to Advance Conservation Science and Practice Program.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/19/2024
|
08/19/2024
|
None
|
Grant
|
47.074
|
1
|
4900
|
4900
|
2430283
|
{'FirstName': 'Dana', 'LastName': 'Morin', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Dana J Morin', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A048M', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Mississippi State University', 'CityName': 'MISSISSIPPI STATE', 'ZipCode': '39762', 'PhoneNumber': '6623257404', 'StreetAddress': '245 BARR AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Mississippi', 'StateCode': 'MS', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'MS03', 'ORG_UEI_NUM': 'NTXJM52SHKS7', 'ORG_LGL_BUS_NAME': 'MISSISSIPPI STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Mississippi State University', 'CityName': 'MISSISSIPPI STATE', 'StateCode': 'MS', 'ZipCode': '39762', 'StreetAddress': '245 BARR AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Mississippi', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'MS03'}
|
{'Code': '727500', 'Text': 'Cross-BIO Activities'}
|
2024~251552
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430283.xml'}
|
Leveraging the Mosquito Holobiont to Suppress Disease and Advance Avian Conservation
|
NSF
|
11/01/2024
|
10/31/2027
| 651,084 | 651,084 |
{'Value': 'Standard Grant'}
|
{'Code': '08090000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'IOS', 'LongName': 'Division Of Integrative Organismal Systems'}}
|
{'SignBlockName': 'Kari Segraves', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928935'}
|
The project will determine how microbes change the response of their host organism to climate change. This research focuses on Hawaiian honeycreepers, a diverse group of birds. Honeycreepers are important in sustaining Hawaiian ecosystems and the cultural identity of indigenous Hawaiians. However, over half of the species have gone extinct, and most of the remaining species face imminent extinction. The driver of this extinction crisis is an introduced avian malaria parasite transmitted by an invasive mosquito species. Government and community partners are working together to suppress mosquitoes and prevent avian malaria transmission. Mosquitoes are being suppressed by releasing sterile males into the environment. These males are sterile because they have a bacterium that lives inside their cells. When male mosquitoes with these bacteria are released, they mate with wild females and decrease their reproduction. However, ecological knowledge gaps may limit the plan’s efficacy. This project will fill these gaps by determining where to release of these male mosquitoes on the landscape and how to increase their mating success following release. This project has broad implications for the management of mosquito-borne diseases, including those that affect human health. In addition, this project will engage in workforce development with native Hawaiians to help restore natural resource management agency to this indigenous group.<br/><br/>The central hypothesis of this research is that microorganisms underlie the response of macroorganisms to a changing environment. This hypothesis is tested using mosquito populations of the avian malaria vector, Culex quinquefasciatus, across gradients in temperature and humidity that vary dramatically with elevation in Hawaii. The first aim clarifies the landscape-scale Cx. quinquefasciatus population dynamics by using metagenomic data to infer whether the mosquito holobiont covaries with elevation in a Hawaiian forest, a pattern consistent with local adaptation or acclimation of the holobiont to environmental regimes. In addition, genomic data and stable isotope tracking will be employed to resolve the connectivity of Cx. quinquefasciatus populations across this mountainous landscape to understand mosquito dispersal and its ramifications for the spread of microbial symbionts, including avian malaria parasites. The second aim manipulates the microbiome component of Cx. quinquefasciatus to understand its impact on adult mosquito phenotypes that influence the performance of the mosquito in its environment. Through controlled laboratory, microbiome transplantation, and common garden experiments, this work will clarify how the mosquito microbiome influences mosquito fitness in cool, high elevation environments where they currently cooccur with native Hawaiian honeycreepers. The third aim monitors the implementation of incompatible insect technique on Kauai, Hawaii to suppress Cx. quinquefasciatus populations in Hawaiian honeycreeper habitat. This effort will document the efficacy of this technique and inform mathematical models that will be used to hone future incompatible insect technique implementation in Hawaii and beyond.<br/><br/>This project is jointly funded by the Divisions of Environmental Biology and Integrative Organismal Systems through the Partnership to Advance Conservation Science and Practice Program.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/19/2024
|
08/19/2024
|
None
|
Grant
|
47.074
|
1
|
4900
|
4900
|
2430326
|
[{'FirstName': 'Matthew', 'LastName': 'Medeiros', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Matthew Medeiros', 'EmailAddress': '[email protected]', 'NSF_ID': '000729959', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Mona Renee', 'LastName': 'Bellinger', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Mona Renee Bellinger', 'EmailAddress': '[email protected]', 'NSF_ID': '000743253', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Katherine', 'LastName': 'McClure', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Katherine M McClure', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A04X9', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'University of Hawaii', 'CityName': 'HONOLULU', 'ZipCode': '968222247', 'PhoneNumber': '8089567800', 'StreetAddress': '2425 CAMPUS RD SINCLAIR RM 1', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Hawaii', 'StateCode': 'HI', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'HI01', 'ORG_UEI_NUM': 'NSCKLFSSABF2', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF HAWAII', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Hawaii', 'CityName': 'HONOLULU', 'StateCode': 'HI', 'ZipCode': '968222247', 'StreetAddress': 'Isabella Aiona Abbott Building', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Hawaii', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'HI01'}
|
{'Code': '727500', 'Text': 'Cross-BIO Activities'}
|
2024~651084
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430326.xml'}
|
CAREER: Enabling Dynamic, Adaptive, and Reliable Battery-free Embedded Computing
|
NSF
|
10/01/2023
|
02/28/2027
| 631,886 | 211,646 |
{'Value': 'Continuing Grant'}
|
{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}
|
{'SignBlockName': 'Jason Hallstrom', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032920000'}
|
For decades, embedded computing and sensing systems have relied primarily on battery power. Yet, batteries are bulky, expensive, high-maintenance, and not sustainable for the next trillion devices. Instead of relying on energy stored in a battery, an emerging class of computing devices harvests all energy needed for operation from sources such as the sun, motion, radio waves, and vibration. However, building sophisticated applications on these battery-free systems is challenging due to frequent power failures from fluctuations in energy harvesting. Programmers must figure out how to string together fragments of execution to meet application goals while dealing with novel software and hardware bugs that stem from power failures. Because of this, memory-intensive, inference-heavy, and user-facing applications have rarely materialized on battery-free devices. New general-purpose hardware platforms with accelerators and heterogeneous computing modules are needed to build these applications. However, hardware is not enough. With new hardware comes new challenges like scalability, dynamism, and memory-efficient checkpointing. This project explores intermittent computing systems and toolchain support for integrating diverse computing modules, like FPGAs, Accelerators, and Vector Processors, alongside traditional microcontrollers. The project weaves scalability across the intermittent computing system stack, leveraging these new modules to enable reactive, adaptive, and high-performance applications on this important new class of computing devices. This project will explore and prototype scalable hardware platforms, adaptive software systems, high-level programming languages, and energy introspection tools that enable even novice developers to quickly prototype sophisticated battery-free applications, despite power failures. These advancements will be demonstrated and evaluated in the context of real-world deployments in mobile health, habitat monitoring, and interactive devices.<br/><br/>Battery-free embedded systems offer a transformative and ecologically sustainable approach for building the next trillion computing devices. This project fills a gap for system designers who lack the hardware platforms, efficient runtime systems, and focused tools to build capable, data-intensive, reactive, and reliable applications with these devices. The results of this research will impact fields across scientific and industrial interests: including healthcare (wearable and body sensor networks), ecology, horticulture, infrastructure, conservation, and public utility monitoring, and many other areas where long-term, massive scale sensing is essential. The hardware, systems, and tools will speed up research and commercialization in critical sectors like smart cities and the Internet of Things. The project's demonstration applications, including smart health devices, interactive devices, and novice-focused programming environments, will provide proof of approach to encourage uptake of battery-free devices. The project includes outreach and education initiatives focused on increasing participation among Native Hawaiian youth in computing by introducing computing concepts via building sustainable and conservation-focused embedded systems applications in partnership with a Native Hawaiian serving public school and non-profit organizations.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
04/30/2024
|
04/30/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2430327
|
{'FirstName': 'Josiah', 'LastName': 'Hester', 'PI_MID_INIT': 'D', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Josiah D Hester', 'EmailAddress': '[email protected]', 'NSF_ID': '000753638', 'StartDate': '04/30/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Georgia Tech Research Corporation', 'CityName': 'ATLANTA', 'ZipCode': '303186395', 'PhoneNumber': '4048944819', 'StreetAddress': '926 DALNEY ST NW', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Georgia', 'StateCode': 'GA', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'GA05', 'ORG_UEI_NUM': 'EMW9FC8J3HN4', 'ORG_LGL_BUS_NAME': 'GEORGIA TECH RESEARCH CORP', 'ORG_PRNT_UEI_NUM': 'EMW9FC8J3HN4'}
|
{'Name': 'Georgia Tech Research Corporation', 'CityName': 'ATLANTA', 'StateCode': 'GA', 'ZipCode': '303320315', 'StreetAddress': '926 DALNEY ST NW', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Georgia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'GA05'}
|
[{'Code': '171400', 'Text': 'Special Projects - CNS'}, {'Code': '735400', 'Text': 'CSR-Computer Systems Research'}]
|
2022~211646
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430327.xml'}
|
Collaborative Research: PACSP: Looking back to move forward - integrating genomics into long-term diversity monitoring of grizzly bears
|
NSF
|
09/01/2024
|
08/31/2029
| 511,998 | 511,998 |
{'Value': 'Standard Grant'}
|
{'Code': '08090000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'IOS', 'LongName': 'Division Of Integrative Organismal Systems'}}
|
{'SignBlockName': 'Melissa J Coleman', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922657'}
|
Brown bears (Ursus arctos) have undergone rapid population declines over the last 150 years in the lower 48 states. This project will use DNA sequencing technologies to investigate the effects of this rapid population decline as well as the effects of previous conservation management actions. The researchers will investigate the utility of these genetic technologies for population monitoring and management. New genetic tools will be developed to rapidly sequence and identify individual brown bears in the lower 48 states using non-invasive samples. Samples from both historical (museum) and contemporary populations will be used to better understand the impact of population decline and conservation management efforts on the health of brown bear populations. The project will yield new insights into how small populations of animals can persist and will include a database with applications for general population monitoring and human-wildlife conflict scenarios. This project will also establish a brown bear genetic database and provide training opportunities in genetic and genomic technologies to conservation managers.<br/><br/>Genomics is poised to be a potentially useful and cost-effective tool for population monitoring and management, however, the limitations of population genetic estimates for conservation purposes are not well understood. This project will use an extensive set of historic and modern brown bear (Ursus arctos) samples to characterize genomic diversity over the last 200 years, how it has changed over time and whether management decisions (e.g., translocations) have impacted the genomic landscape of the species. Brown bears in the lower 48 have been extensively monitored since approximately 1975. The life history data collected by conservation partners over the past several decades, paired with newly collected genomic data, will be used to analyze the impact of past translocations and population bottlenecks in the lower 48. Relating population genetic statistics to life history traits, such as fecundity, lifespan, and independent population size estimates, will help to better implement recommendations to maintain genetic health for species of conservation concern.<br/><br/>This project is jointly funded by the Division of Environmental Biology and Integrative Organismal Systems through the Partnership to Advance Conservation Science and Practice Program.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/19/2024
|
08/19/2024
|
None
|
Grant
|
47.074
|
1
|
4900
|
4900
|
2430336
|
[{'FirstName': 'Joanna', 'LastName': 'Kelley', 'PI_MID_INIT': 'L', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Joanna L Kelley', 'EmailAddress': '[email protected]', 'NSF_ID': '000443402', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Michael', 'LastName': 'Campana', 'PI_MID_INIT': 'G', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Michael G Campana', 'EmailAddress': '[email protected]', 'NSF_ID': '000736312', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'University of California-Santa Cruz', 'CityName': 'SANTA CRUZ', 'ZipCode': '950641077', 'PhoneNumber': '8314595278', 'StreetAddress': '1156 HIGH ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '19', 'CONGRESS_DISTRICT_ORG': 'CA19', 'ORG_UEI_NUM': 'VXUFPE4MCZH5', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CALIFORNIA SANTA CRUZ', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of California-Santa Cruz', 'CityName': 'SANTA CRUZ', 'StateCode': 'CA', 'ZipCode': '950641077', 'StreetAddress': '1156 HIGH ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '19', 'CONGRESS_DISTRICT_PERF': 'CA19'}
|
{'Code': '727500', 'Text': 'Cross-BIO Activities'}
|
2024~511998
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430336.xml'}
|
Collaborative Research: PACSP: Looking back to move forward - integrating genomics into long-term diversity monitoring of grizzly bears
|
NSF
|
09/01/2024
|
08/31/2029
| 413,621 | 413,621 |
{'Value': 'Standard Grant'}
|
{'Code': '08090000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'IOS', 'LongName': 'Division Of Integrative Organismal Systems'}}
|
{'SignBlockName': 'Melissa J Coleman', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922657'}
|
Brown bears (Ursus arctos) have undergone rapid population declines over the last 150 years in the lower 48 states. This project will use DNA sequencing technologies to investigate the effects of this rapid population decline as well as the effects of previous conservation management actions. The researchers will investigate the utility of these genetic technologies for population monitoring and management. New genetic tools will be developed to rapidly sequence and identify individual brown bears in the lower 48 states using non-invasive samples. Samples from both historical (museum) and contemporary populations will be used to better understand the impact of population decline and conservation management efforts on the health of brown bear populations. The project will yield new insights into how small populations of animals can persist and will include a database with applications for general population monitoring and human-wildlife conflict scenarios. This project will also establish a brown bear genetic database and provide training opportunities in genetic and genomic technologies to conservation managers.<br/><br/>Genomics is poised to be a potentially useful and cost-effective tool for population monitoring and management, however, the limitations of population genetic estimates for conservation purposes are not well understood. This project will use an extensive set of historic and modern brown bear (Ursus arctos) samples to characterize genomic diversity over the last 200 years, how it has changed over time and whether management decisions (e.g., translocations) have impacted the genomic landscape of the species. Brown bears in the lower 48 have been extensively monitored since approximately 1975. The life history data collected by conservation partners over the past several decades, paired with newly collected genomic data, will be used to analyze the impact of past translocations and population bottlenecks in the lower 48. Relating population genetic statistics to life history traits, such as fecundity, lifespan, and independent population size estimates, will help to better implement recommendations to maintain genetic health for species of conservation concern.<br/><br/>This project is jointly funded by the Division of Environmental Biology and Integrative Organismal Systems through the Partnership to Advance Conservation Science and Practice Program.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/19/2024
|
08/19/2024
|
None
|
Grant
|
47.074
|
1
|
4900
|
4900
|
2430337
|
{'FirstName': 'Ellie', 'LastName': 'Armstrong', 'PI_MID_INIT': 'E', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ellie E Armstrong', 'EmailAddress': '[email protected]', 'NSF_ID': '000941797', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of California-Riverside', 'CityName': 'RIVERSIDE', 'ZipCode': '925210001', 'PhoneNumber': '9518275535', 'StreetAddress': '200 UNIVERSTY OFC BUILDING', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '39', 'CONGRESS_DISTRICT_ORG': 'CA39', 'ORG_UEI_NUM': 'MR5QC5FCAVH5', 'ORG_LGL_BUS_NAME': 'REGENTS OF THE UNIVERSITY OF CALIFORNIA AT RIVERSIDE', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of California-Riverside', 'CityName': 'RIVERSIDE', 'StateCode': 'CA', 'ZipCode': '925210001', 'StreetAddress': '200 UNIVERSTY OFC BUILDING', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '39', 'CONGRESS_DISTRICT_PERF': 'CA39'}
|
{'Code': '727500', 'Text': 'Cross-BIO Activities'}
|
2024~413621
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430337.xml'}
|
AF:Small:Learning from Dynamics
|
NSF
|
10/01/2024
|
09/30/2027
| 600,000 | 600,000 |
{'Value': 'Standard Grant'}
|
{'Code': '05010000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CCF', 'LongName': 'Division of Computing and Communication Foundations'}}
|
{'SignBlockName': 'Tracy Kimbrel', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032920000'}
|
Over recent years, there has been remarkable progress in providing algorithms with provable guarantees for various fundamental machine learning problems. These problems are often of an unsupervised flavor (i.e., are given unlabeled data and look for patterns and insights without any explicit guidance), and the samples come from some unknown but fixed distribution. Yet, there are important problems coming from signal processing, control theory, and natural language processing that do not fit into this mold because the data arrives in a sequence with a rich dependency structure. The goal of this project is to design better algorithms for such problems by building the appropriate bridges to the tools and perspectives in more classic settings. This project will also involve training the next generation of graduate students and equipping them with the technical tools to work at the cutting edge of theoretical machine learning. The investigator will also revise his free online graduate textbook with material from recent progress related to this project.<br/><br/>This project explores learning problems for linear dynamical systems, graphical models, and hidden Markov models. The team will prove rigorous guarantees for methods like prefiltered least squares as well as study what happens when our observations are intermittent and the usual algebraic structure is unavailable. They will also show how learning from the Glauber dynamics makes it possible to circumvent known computational lower bounds for learning higher-order graphical models. And, finally, the team will study how hidden Markov models can be learned using a conditional sampling oracle. As a byproduct, this project will export technical ideas from theoretical computer science into areas where there are currently wide gaps in our algorithmic understanding.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/22/2024
|
07/22/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2430381
|
{'FirstName': 'Ankur', 'LastName': 'Moitra', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ankur Moitra', 'EmailAddress': '[email protected]', 'NSF_ID': '000649382', 'StartDate': '07/22/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Massachusetts Institute of Technology', 'CityName': 'CAMBRIDGE', 'ZipCode': '021394301', 'PhoneNumber': '6172531000', 'StreetAddress': '77 MASSACHUSETTS AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MA07', 'ORG_UEI_NUM': 'E2NYLCDML6V1', 'ORG_LGL_BUS_NAME': 'MASSACHUSETTS INSTITUTE OF TECHNOLOGY', 'ORG_PRNT_UEI_NUM': 'E2NYLCDML6V1'}
|
{'Name': 'Massachusetts Institute of Technology', 'CityName': 'CAMBRIDGE', 'StateCode': 'MA', 'ZipCode': '021394301', 'StreetAddress': '77 MASSACHUSETTS AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MA07'}
|
{'Code': '779600', 'Text': 'Algorithmic Foundations'}
|
2024~600000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430381.xml'}
|
Elucidating how species interactions influence the success or failure of invasion into microbial communities
|
NSF
|
09/01/2024
|
08/31/2028
| 788,966 | 788,966 |
{'Value': 'Standard Grant'}
|
{'Code': '08070000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'MCB', 'LongName': 'Div Of Molecular and Cellular Bioscience'}}
|
{'SignBlockName': 'David J. Klinke', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922890'}
|
In recent years there has been a growing understanding of microbes’ potentials to address societal challenges, from ecosystem sustainability to public health to industrial production. Microbial functions often happen in communities of multiple microbial types, and to assemble and maintain such communities, it is important to know how to add a microbe of interest to an existing community and how to protect a community from invaders. However, developing this know-how is hard because of the complexity of natural communities: there are often many microbial types and how they affect each other is often poorly understood. In this project, a simplified microbial community of microbes usually present in the human nose is used as a laboratory model to study what allows a microbe to establish into an existing community. For this, mathematical models of biological communities along with quantitative microbiology experiments will be used to clarify how microbial interactions determine whether newcomers into an existing community succeed or fail. Insights developed in this project teach us more about how microbial communities work and allow us to design and control such communities for a wide range of applications, including recycling waste products, preventing human diseases, and producing valuable compounds using microbes. <br/><br/>Biological invasion—a new organism colonizing a resident community—can be a major driving force for community restructuring and can be desired (e.g. when introducing probiotic/biocontrol strains) or undesired (e.g. when encountering pathogens). An improved understanding of how underlying processes such as species interaction can determine the invasion outcomes will enable us to implement biocontrol strategies in ecosystem sustainability, industrial bioproduction, and human health. Despite many previous studies of invasion, the know-how of designing effective interventions to alter invasion outcomes is still missing. The goal of this project is to investigate how invasion outcomes are influenced by species interactions such as competition for resources or facilitation/inhibition via metabolic byproducts. Through a combination of mathematical modeling and experimental validation using laboratory communities of nasal bacteria, three fundamental questions will be investigated: (1) Can changing the overall nutrient availability influence invasion outcomes? (2) Is estimating ecological interactions from community dynamics sufficient to predict invasion outcomes? (3) Are there critical interactions that control invasion outcomes? In addition to these scientific discoveries, the project contributes to training interdisciplinary researchers, developing community resources such as public blogs and databases, and raising awareness in the general public about the power of harnessing microbial potentials. This project is supported by the Systems and Synthetic Biology Cluster of the Division of Molecular and Cellular Biosciences.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/06/2024
|
08/06/2024
|
None
|
Grant
|
47.074
|
1
|
4900
|
4900
|
2430384
|
{'FirstName': 'Babak', 'LastName': 'Momeni', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Babak Momeni', 'EmailAddress': '[email protected]', 'NSF_ID': '000737150', 'StartDate': '08/06/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Boston College', 'CityName': 'CHESTNUT HILL', 'ZipCode': '024673800', 'PhoneNumber': '6175528000', 'StreetAddress': '140 COMMONWEALTH AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'MA04', 'ORG_UEI_NUM': 'MJ3JH8CRJBZ7', 'ORG_LGL_BUS_NAME': 'TRUSTEES OF BOSTON COLLEGE', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Trustees of Boston College', 'CityName': 'CHESTNUT HILL', 'StateCode': 'MA', 'ZipCode': '024673800', 'StreetAddress': '140 COMMONWEALTH AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'MA04'}
|
{'Code': '801100', 'Text': 'Systems and Synthetic Biology'}
|
2024~788966
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430384.xml'}
|
I-Corps: Translation potential of using generative models for automatic test question generation and evaluation for educational assessment applications
|
NSF
|
06/01/2024
|
05/31/2025
| 50,000 | 50,000 |
{'Value': 'Standard Grant'}
|
{'Code': '15030000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'TI', 'LongName': 'Translational Impacts'}}
|
{'SignBlockName': 'Jaime A. Camelio', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922061'}
|
The broader impact of this I-Corps project is the development of an intelligent test question development assistant, which could potentially support K-12 test developers by automatically generating high-quality questions and responses. This solution would benefit the testing and educational support industry, including but not limited to K-12 testing companies, language testing agencies, online education platforms, professional certifiers and licensure groups, and classroom teachers. The time and cost of test development would be significantly reduced. The technology will help advance the development and adoption of generative artificial intelligence techniques in educational measurement and assessment, contributing to the next generation of artificial intelligence tools for education. <br/><br/>This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. This solution is based on the development of a generative artificial intelligence tool for test question development and evaluation for educational assessment applications. Test question development has been recognized as an extremely time-consuming, labor intensive, and expensive process in traditional paper-and-pencil testing and computerized adaptive testing. Automatic generation and evaluation of test questions presents a promising solution and has attracted considerable attention in the past decade. This automatic question generation and evaluation system leverages customized large foundation models to generate question for various educational assessment tasks, such as K-12 standardized tests and language tests. In addition, the system is able to generate high-quality test questions that are well aligned with user specifications, such as test blueprints, fairness, and difficulty levels.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
05/21/2024
|
05/21/2024
|
None
|
Grant
|
47.084
|
1
|
4900
|
4900
|
2430387
|
{'FirstName': 'Sheng', 'LastName': 'Li', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Sheng Li', 'EmailAddress': '[email protected]', 'NSF_ID': '000785205', 'StartDate': '05/21/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Virginia Main Campus', 'CityName': 'CHARLOTTESVILLE', 'ZipCode': '229034833', 'PhoneNumber': '4349244270', 'StreetAddress': '1001 EMMET ST N', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Virginia', 'StateCode': 'VA', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'VA05', 'ORG_UEI_NUM': 'JJG6HU8PA4S5', 'ORG_LGL_BUS_NAME': 'RECTOR & VISITORS OF THE UNIVERSITY OF VIRGINIA', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Virginia Main Campus', 'CityName': 'CHARLOTTESVILLE', 'StateCode': 'VA', 'ZipCode': '229034833', 'StreetAddress': '1001 EMMET ST N', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Virginia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'VA05'}
|
{'Code': '802300', 'Text': 'I-Corps'}
|
2024~50000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430387.xml'}
|
Tunable Wavelength GeSn Laser and Photodetector on Lattice-Matched InAl(Ga)As Buffers for Group-IV Photonics
|
NSF
|
09/01/2024
|
08/31/2027
| 450,000 | 450,000 |
{'Value': 'Standard Grant'}
|
{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}
|
{'SignBlockName': 'Dominique Dagenais', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922980'}
|
In line with the recent CHIPS and Science Act of 2022 and the push for quantum technology, group IV-based GeSn semiconductor materials have potential in photonics due to their unique and wide range of optical characteristics achieved by bandgap engineering via control of tin (Sn) composition in the GeSn alloy. The continued development of compact and affordable laser light sources and detection based on GeSn materials is important in many areas such as communication, biomedical, and defense applications. However, one needs to synthesize device-quality, low-defect density tunable Sn compositional GeSn materials on a lattice-matched buffer. Furthermore, there is a lack of low-threshold current density GeSn-based laser light source due to the low carrier lifetime and weak carrier confinement on silicon that demand investigation of an alternative GeSn heterostructure design, which can achieve much higher conversion efficiency, thereby enhancing the integrated photonic device performance. The latticed-matched combination of GeSn and InAl(Ga)As heterostructures for laser and photodetector offers a new path for highly efficient tunable light emission and detection. The central thrust of the proposed research is to investigate the design of tunable Sn compositional GeSn-based laser and mid-wavelength infra-red (MWIR) photodetector architectures that combine GeSn quantum-well (QW) or absorber layer lattice-matched to underlying InAl(Ga)As buffer. Our objective is to develop tunable wavelength laser light sources that can exhibit lower threshold current density and higher quantum efficiency than existing group IV-based light sources as well as MWIR detection that will benefit a wide range of applications.<br/><br/> To demonstrate the feasibility of the proposed approach, several key technical and scientific challenges must be addressed, including (i) low-defect density tunable Sn compositional GeSn layer on lattice-matched InAl(Ga)As buffer with enhanced carrier lifetime; (ii) increased band offsets between GeSn and large bandgap InAl(Ga)As barrier layer for superior carrier confinement in a GeSn QW; (iii) design and simulation of the proposed wavelength tunability of GeSn/InAl(Ga)As-based QW laser and MWIR GeSn-based photodetectors; (iv) materials synthesis and analysis of lattice-matched InAl(Ga)As/GeSn/InAl(Ga)As QW laser structure on GaAs for modified bandgap of GeSn; and (v) fabrication and demonstration of GeSn QW laser and photodetector. To address (i), (ii), (iv), and (v), the proposed research will utilize the state-of-the-art in-house epitaxial growth (interconnected III-V and group IV molecular beam epitaxy chambers), comprehensive materials characterization and simulation (e.g., high-resolution x-ray diffraction, transmission electron microscopy, photoconductive decay, photoluminescence spectroscopy, atom probe tomography, x-ray photoelectron spectroscopy, and electronic band structure simulation by QuantumATK), and in-house fabrication facilities. To address (iii), a combination of numerical simulations (Synopsys TCAD) and density functional theory will be leveraged to develop experimentally-calibrated InAl(Ga)As/GeSn/InAl(Ga)As QW device models necessary for light emission in MWIR range and photodetection. By investigating these topics, this research will elucidate numerous as-of-yet unexplored avenues of fundamental research, including (a) the synthesis of high Sn compositional GeSn alloy on lattice-matched InAl(Ga)As buffer; (b) the role of GeSn layer thickness to optical gain and emission wavelength; (c) the reduction of threshold current density arising from recombination losses; (d) carrier lifetime and interatomic diffusion in a GeSn alloy on InAl(Ga)As buffer. Through a comprehensive examination and understanding of the above challenges, this research will establish a pathway to achieve high-performance group IV lasers and detectors that will benefit society and industry. Furthermore, this project will train and mentor undergraduate and graduate students in the field of photonics. These students will experience a research environment in PI’s laboratories. Outcomes of the proposed research results will be disseminated to the public and be incorporated into the course curriculum. In addition, the project will provide hands-on experience to undergraduates through Virginia Tech ECE Department major design experience.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/25/2024
|
07/25/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2430393
|
{'FirstName': 'Mantu', 'LastName': 'Hudait', 'PI_MID_INIT': 'K', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Mantu K Hudait', 'EmailAddress': '[email protected]', 'NSF_ID': '000545553', 'StartDate': '07/25/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Virginia Polytechnic Institute and State University', 'CityName': 'BLACKSBURG', 'ZipCode': '240603359', 'PhoneNumber': '5402315281', 'StreetAddress': '300 TURNER ST NW', 'StreetAddress2': 'STE 4200', 'CountryName': 'United States', 'StateName': 'Virginia', 'StateCode': 'VA', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_ORG': 'VA09', 'ORG_UEI_NUM': 'QDE5UHE5XD16', 'ORG_LGL_BUS_NAME': 'VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'M515A1DKXAN8'}
|
{'Name': 'Virginia Polytechnic Institute and State University', 'CityName': 'BLACKSBURG', 'StateCode': 'VA', 'ZipCode': '240603359', 'StreetAddress': '300 TURNER ST NW', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Virginia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_PERF': 'VA09'}
|
{'Code': '151700', 'Text': 'EPMD-ElectrnPhoton&MagnDevices'}
|
2024~450000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430393.xml'}
|
Design and Realization of Multiplexed Meta-Optical Neural Networks
|
NSF
|
08/01/2024
|
07/31/2027
| 467,930 | 467,930 |
{'Value': 'Standard Grant'}
|
{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}
|
{'SignBlockName': 'Ale Lukaszew', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928103'}
|
Artificial neural networks in machine learning have impacted many fields of science and engineering. Despite tremendous progress and achievements, implementing artificial neural networks on conventional computers is becoming increasingly challenging due to power and speed constraints. Optical neural networks (ONNs), which offer potential advantages in energy efficiency, speed, parallelism, bandwidth, and scalability, stand out as a highly promising solution to this challenge. The goal of this project is to design and implement a novel class of metasurface-based ONNs, termed meta-ONNs, which can operate at optical frequencies and realize diverse functions, including all-optical image recognition and pattern generation. Metasurfaces are composed of artificially engineered structures much smaller than the wavelength of light. They can manipulate light characteristics such as the amplitude, polarization state, and phase in a prescribed manner. By leveraging the unique properties of metasurfaces, this project will demonstrate innovative meta-ONNs capable of encoding multiple functional channels within a single system and achieving functions beyond conventional classification, significantly expanding the capabilities of ONNs by transforming computing, communications, and information processing technologies, thus benefiting the public and the nation. Integrated with the research, the education effort of the project will enhance outreach activities and educate students across different levels. Students will actively participate in the project, gaining frontier knowledge in multiple fields and eventually becoming leaders in the next-generation workforce.<br/><br/>The project aims to unlock the potential of meta-ONNs as a new platform for multifunctional optical computing, complex information processing, and innovative image generation through a software-hardware co-design approach that seamlessly integrates photonics, neural network models, advanced manufacturing, and systems engineering. The project consists of three research thrusts: (1) Design multiplexed meta-ONNs based on artificial intelligence (AI) and optimization techniques to seamlessly integrate multiple wavelength and polarization channels within a single system, greatly enhancing the capacity and versatility of ONNs; (2) Demonstrate generative meta-ONNs that can create distinct images after light propagates through the meta-ONNs, enabling novel optical encryption schemes and serving as pivotal tools for AI-assisted photonic design; (3) Fabricate low-loss, multilayered metasurfaces to implement the designed meta-ONNs, and experimentally characterize the key performance metrics including accuracy, efficiency, and robustness. The precise control of light at the subwavelength meta-neuron level is expected to significantly boost the capacity of ONNs. New manufacturing methodologies and techniques will be developed to realize high-efficiency meta-ONNs. The potential applications of the meta-ONNs include image generation for virtual reality and entertainment, medical imaging and diagnostics, security and surveillance, autonomous driving, and advanced photonic circuits for quantum computing. The research findings will accelerate the interplay between AI and photonics, forming the virtuous AI-photonics-AI circle. The design principles could also serve as inspiration for other physical neural networks and intelligent devices based on mechanical, electrical, and acoustic systems.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/31/2024
|
07/31/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2430412
|
{'FirstName': 'Yongmin', 'LastName': 'Liu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Yongmin Liu', 'EmailAddress': '[email protected]', 'NSF_ID': '000636028', 'StartDate': '07/31/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Northeastern University', 'CityName': 'BOSTON', 'ZipCode': '021155005', 'PhoneNumber': '6173733004', 'StreetAddress': '360 HUNTINGTON AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MA07', 'ORG_UEI_NUM': 'HLTMVS2JZBS6', 'ORG_LGL_BUS_NAME': 'NORTHEASTERN UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Northeastern University', 'CityName': 'BOSTON', 'StateCode': 'MA', 'ZipCode': '021155005', 'StreetAddress': '360 HUNTINGTON AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MA07'}
|
{'Code': '756400', 'Text': 'CCSS-Comms Circuits & Sens Sys'}
|
2024~467930
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430412.xml'}
|
EAGER: TaskDCL: Simultaneous Use of Synthetic Actors for Multimodal Cueing of Sensory-Motor Interactions in Pilot Training
|
NSF
|
09/01/2024
|
08/31/2026
| 300,000 | 300,000 |
{'Value': 'Standard Grant'}
|
{'Code': '07030000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CMMI', 'LongName': 'Div Of Civil, Mechanical, & Manufact Inn'}}
|
{'SignBlockName': 'Alexandra Medina-Borja', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927557'}
|
The goal of this EArly-concept Grant for Exploratory Research (EAGER) grant is to enhance pilot training by developing methods to optimize sensory-motor interactions, thereby reducing training duration through accelerated learning. Traditional pilot training mainly relies on dominant sensory cues like vision and equilibrium. This research explores how secondary sensory cues, such as the senses of touch and audition, can be used to improve training efficiency. Additionally, the project seeks to leverage insights into pilot neurophysiology to better integrate these sensory cues in real time. By applying principles from flight dynamics, control theory, human-machine interaction, and neurophysiology, this project aims to create a comprehensive framework for optimizing sensory-motor interactions. This research supports the national interest by advancing science and promoting public welfare through improved training methods that enhance safety and efficiency in aviation. This study is particularly relevant as it supports the strategic transition towards Single Pilot Operations, which are projected for future passenger airplanes and next-generation rotorcraft aimed at Urban Air Mobility, commonly referred to as air taxis. Broader impacts include developing digital assistant systems that adapt to the cognitive workload of operators, reducing training costs, and improving safety in complex environments.<br/><br/>The specific objective of this research project is to develop methods for optimizing sensory-motor interaction strategies to minimize pilot training duration. This involves creating a pilot training platform that uses multiple synthetic actors for neuroadaptive multimodal cueing. In this setup, a human pilot collaborates with an intelligent agent to control a simulated vehicle, functioning as a symbiotic organism. The vehicle can be any machine capable of moving across regions of physical space such as airplanes, helicopters, or drones. The pilot receives multimodal cues through five synthetic actors: virtual and augmented reality goggles for visual cues, a motion-base platform for proprioceptive cues, spatial audio headphones for auditory cues, full-body haptic suits for haptic feedback, and active control inceptors for additional haptic cues. Real-time neuroadaptation enables the intelligent agent to adjust these cues and its control authority based on the pilot’s cognitive and physiological states and the performance of the pilot-vehicle system. This approach integrates tools from flight dynamics, control theory, human-machine interaction, and neurophysiology to develop a framework for optimal sensory-motor interaction. The project introduces several novel aspects, including the simultaneous use of multiple synthetic actors in sensory-motor interaction, the application of secondary sensory cues, and the adaptive modification of multimodal cues based on real-time data. The anticipated outcomes include advancements in digital assistant systems, improved training methods, and enhanced operational safety.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/09/2024
|
08/09/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2430418
|
{'FirstName': 'Umberto', 'LastName': 'Saetti', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Umberto Saetti', 'EmailAddress': '[email protected]', 'NSF_ID': '000918962', 'StartDate': '08/09/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Maryland, College Park', 'CityName': 'COLLEGE PARK', 'ZipCode': '207425100', 'PhoneNumber': '3014056269', 'StreetAddress': '3112 LEE BUILDING', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Maryland', 'StateCode': 'MD', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'MD04', 'ORG_UEI_NUM': 'NPU8ULVAAS23', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF MARYLAND, COLLEGE PARK', 'ORG_PRNT_UEI_NUM': 'NPU8ULVAAS23'}
|
{'Name': 'University of Maryland', 'CityName': 'COLLEGE PARK', 'StateCode': 'MD', 'ZipCode': '207421800', 'StreetAddress': '4298 Campus Drive', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Maryland', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'MD04'}
|
[{'Code': '058Y00', 'Text': 'M3X - Mind, Machine, and Motor'}, {'Code': '164200', 'Text': 'Special Initiatives'}]
|
2024~300000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430418.xml'}
|
Non-Invasive Models of Human Brain-Computer-Interface Control of Robots
|
NSF
|
01/01/2024
|
11/30/2025
| 480,000 | 324,028 |
{'Value': 'Standard Grant'}
|
{'Code': '07030000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CMMI', 'LongName': 'Div Of Civil, Mechanical, & Manufact Inn'}}
|
{'SignBlockName': 'Alexandra Medina-Borja', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927557'}
|
There are many situations where a skilled human operator must manipulate a large number of control variables in real-time to direct the dexterous motion of a robotic device. These include controlling an excavator, teleoperating a surgical robot, and operating a cutting-edge brain-controlled prosthetic limb. However, it remains unknown how large sets of control variables can be organized to optimize how people learn to control complex machines. This project seeks to promote the progress of science and advance the national health by addressing two questions related to the design and implementation of adaptive brain-machine-interfaces such as those used by severely impaired people to control assistive robotics. An important novelty of the researched approach is the non-invasive recording of finger motions as a proxy for the high-dimensional inputs typically provided by intracortical brain-computer interfaces (iBCI). The specific research questions addressed by this project include: 1) "How should control signals be presented to the user at the control interface to optimize output behavior of the machine?", and 2) "Should the robotic system predict what the user wants it to do and adapt its behavior accordingly, and if so, how should task-level control be shared between the user and the machine to optimize task performance?". Project outcomes promise to be applicable to a wide range of difficult human-machine interaction problems. The awardee's institution is a Hispanic Serving Institution; the research includes outreach activities that specifically engage underrepresented groups, undergraduate students, and the local community.<br/><br/>The project will use two models of intracortical brain-computer interfaces (iBCI) to evaluate how high-dimensional human input should be mapped onto command variables for a 6 degree-of-freedom embodied robotic arm. The project uses non-invasive recording of finger motions as a proxy for the high-dimensional inputs typically provided by iBCIs. The first model linearly projects finger articulations into one of seven different robot command spaces (effector position, joint velocity, motor torques, etc.). The project team will evaluate how human subjects perform with the assistive robot on tasks of daily living (e.g., moving objects on a tabletop or bringing a cup to their mouth) with each of the seven different interfaces. By doing so, they will determine the role that command space encoding plays in the rate of human learning and the ultimate extent of task proficiency. The second model acquires human kinematic input to drive a deep neural network model of motor cortex neurons, whose firing rates are then passed through a decoding algorithm to infer commands for the robot; this is an explicit and validated model of intracortical brain-computer interfaces. The project team will use this model to determine optimal rates of online decoder adaptation to emulated neural input, and the extent to which the adaptation rates interact with the choice of command space in optimizing task performance of the assistive robotic machine.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
05/13/2024
|
05/13/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2430423
|
{'FirstName': 'Zachary', 'LastName': 'Danziger', 'PI_MID_INIT': 'C', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Zachary C Danziger', 'EmailAddress': '[email protected]', 'NSF_ID': '000783305', 'StartDate': '05/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Emory University', 'CityName': 'ATLANTA', 'ZipCode': '303221061', 'PhoneNumber': '4047272503', 'StreetAddress': '201 DOWMAN DR NE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Georgia', 'StateCode': 'GA', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'GA05', 'ORG_UEI_NUM': 'S352L5PJLMP8', 'ORG_LGL_BUS_NAME': 'EMORY UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Emory University', 'CityName': 'ATLANTA', 'StateCode': 'GA', 'ZipCode': '303221061', 'StreetAddress': '201 DOWMAN DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Georgia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'GA05'}
|
{'Code': '058Y00', 'Text': 'M3X - Mind, Machine, and Motor'}
|
2022~324028
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430423.xml'}
|
Conference: Southern California Geometric Analysis Seminar
|
NSF
|
01/01/2025
|
12/31/2025
| 24,998 | 24,998 |
{'Value': 'Standard Grant'}
|
{'Code': '03040000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'DMS', 'LongName': 'Division Of Mathematical Sciences'}}
|
{'SignBlockName': 'Eriko Hironaka', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927041'}
|
This award provides support for the 30th Southern California Geometric Analysis Seminar (SCGAS) meeting, which will be held during the Winter quarter of 2025 at the University of California - Irvine. The SCGAS is an annual two-day conference that rotates between the University of California - Irvine and the University of California - San Diego. The conference features talks given by acclaimed researchers and promotes interactions among members of the Southern California mathematics community working in the field of geometric analysis and related areas. It further seeks to introduce to graduate students and postdoctoral fellows some of the most exciting recent developments in geometric analysis. This funding award is geared towards supporting and encouraging the participation of graduate students and recent PhDs, especially women and under-represented minorities, by providing them the necessary travel support to attend the conference.<br/><br/>Geometric analysis is an important area of modern mathematics and is related to many other branches of mathematics. Using analysis as its main tool along with differential geometry, topology, and algebraic geometry as foundations, geometric analysis has solved a large number of problems in global geometry, topology, several complex variables and mathematical physics. As the success of the first 29 meetings have demonstrated, the SCGAS conference has now become an important and anticipated event for the Southern California region and has also attracted a substantial number of participants from the rest of the country each year. Indeed, it is the unique annual meeting of its kind in the Southern California area, and continues to foster interests in geometric analysis at all levels. In the years past, interactions among the participants during the conference have led to a number of new collaborations and research projects.<br/><br/>The web site for the 30th Southern California Geometric Analysis Seminar may be found at https://www.math.uci.edu/~scgas/.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/31/2024
|
07/31/2024
|
None
|
Grant
|
47.049
|
1
|
4900
|
4900
|
2430426
|
[{'FirstName': 'Zhiqin', 'LastName': 'Lu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Zhiqin Lu', 'EmailAddress': '[email protected]', 'NSF_ID': '000199375', 'StartDate': '07/31/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Jeff', 'LastName': 'Viaclovsky', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jeff A Viaclovsky', 'EmailAddress': '[email protected]', 'NSF_ID': '000366586', 'StartDate': '07/31/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Jeffrey', 'LastName': 'Streets', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jeffrey Streets', 'EmailAddress': '[email protected]', 'NSF_ID': '000549453', 'StartDate': '07/31/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Li Sheng', 'LastName': 'Tseng', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Li Sheng Tseng', 'EmailAddress': '[email protected]', 'NSF_ID': '000602317', 'StartDate': '07/31/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Xiangwen', 'LastName': 'Zhang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Xiangwen Zhang', 'EmailAddress': '[email protected]', 'NSF_ID': '000627747', 'StartDate': '07/31/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'University of California-Irvine', 'CityName': 'IRVINE', 'ZipCode': '926970001', 'PhoneNumber': '9498247295', 'StreetAddress': '160 ALDRICH HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '47', 'CONGRESS_DISTRICT_ORG': 'CA47', 'ORG_UEI_NUM': 'MJC5FCYQTPE6', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CALIFORNIA IRVINE', 'ORG_PRNT_UEI_NUM': 'MJC5FCYQTPE6'}
|
{'Name': 'University of California-Irvine', 'CityName': 'IRVINE', 'StateCode': 'CA', 'ZipCode': '926970001', 'StreetAddress': '160 ALDRICH HALL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '47', 'CONGRESS_DISTRICT_PERF': 'CA47'}
|
{'Code': '126500', 'Text': 'GEOMETRIC ANALYSIS'}
|
2024~24998
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430426.xml'}
|
Training Holistic Research Innovators Via Education Postdoctoral Fellowships in STEM (THRIVE-STEM)
|
NSF
|
10/01/2024
|
09/30/2027
| 1,249,992 | 1,249,992 |
{'Value': 'Standard Grant'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Andrea Nixon', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922321'}
|
Particularly in STEM fields, doctoral programs primarily focus on research training. However, in order to thrive in academic careers scholars are also called upon to play important roles involving teaching, mentoring, and service. This project aims to develop STEM education scholars who have skills, tools, and supports to thrive while contributing to our nation's capacity to conduct STEM education research. This postdoctoral cohort project is designed to support long-term career growth by enabling Fellows to further develop their research and communication skills as well as ways to maintain their mental and social health. The fellowship program will include programming co-developed with research faculty, teaching faculty, and graduate students. In the second year, the program will be further shaped in partnership with the Fellows themselves. <br/> <br/>The project draws upon social learning theory to design an intentional, scaffolded program that will bring scholars deeper into a professional practice community and develop their thriving skills. Fellows supported through this award will engage in a Community of Practice along with current faculty and graduate students. Fellows will also engage in research, proposal writing, and teaching praxis with increasing autonomy as they progress in the two-year program. Through the Community of Practice, scholars will complete tailored activities to address five hidden competencies of thriving: research fundamentals, disciplinary communication, career growth, and managing mental and social health. Additionally, Fellows will participate in the National Center for Faculty Diversity and Development’s Core Program that ties all five hidden competencies together and been shown to enhance researchers’ writing productivity and well-being. The project’s evaluation plan is designed to assess the elements of our program to increase our ability to share its impacts with others who are training STEM education researchers.<br/><br/>This project is funded by the STEM Education Postdoctoral Research Fellowship (STEM Ed PRF) program that aims to enhance the research knowledge, skills, and practices of recent doctorates in STEM, STEM education, education, and related disciplines to advance their preparation to engage in fundamental and applied research that advances knowledge within the field.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/29/2024
|
07/29/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2430431
|
[{'FirstName': 'Cassandra', 'LastName': 'Jamison', 'PI_MID_INIT': 'S', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Cassandra S Jamison', 'EmailAddress': '[email protected]', 'NSF_ID': '000885626', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Jill', 'LastName': 'Perry', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jill A Perry', 'EmailAddress': '[email protected]', 'NSF_ID': '000108471', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Kaitlin', 'LastName': 'Mallouk', 'PI_MID_INIT': 'E', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Kaitlin E Mallouk', 'EmailAddress': '[email protected]', 'NSF_ID': '000719678', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'Rowan University', 'CityName': 'GLASSBORO', 'ZipCode': '080281700', 'PhoneNumber': '8562564057', 'StreetAddress': '201 MULLICA HILL RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New Jersey', 'StateCode': 'NJ', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'NJ01', 'ORG_UEI_NUM': 'DMDEQP66JL85', 'ORG_LGL_BUS_NAME': 'ROWAN UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Rowan University', 'CityName': 'GLASSBORO', 'StateCode': 'NJ', 'ZipCode': '080281700', 'StreetAddress': '201 MULLICA HILL RD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New Jersey', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'NJ01'}
|
{'Code': '713700', 'Text': 'Postdoctoral Fellowships'}
|
2024~1249992
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430431.xml'}
|
Conference: Kylerec Student Workshops in Symplectic and Contact Geometry
|
NSF
|
11/01/2024
|
10/31/2027
| 130,483 | 130,483 |
{'Value': 'Standard Grant'}
|
{'Code': '03040000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'DMS', 'LongName': 'Division Of Mathematical Sciences'}}
|
{'SignBlockName': 'Qun Li', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927465'}
|
The 2025 edition of the Kylerec Graduate Student Workshop is scheduled to take place during the period June 23-27, 2025, near Tahoe, CA, and this award provides support for the next three editions of the workshop (2025, 2026 and 2027). The Kylerec workshop aims to introduce aspiring mathematicians in the fields of symplectic and contact geometry and from many institutions to vibrant areas of research, fostering collaboration, forming strong research ties between young researchers, and thus promoting future collaboration and research. The workshop is specifically designed to encourage the development of a diverse group of researchers in the fields of symplectic and contact geometry. It is a week-long intensive workshop, in which all activities occur under one roof which serves as the mathematical and social center for the week. The lectures are delivered by the graduate student participants with the help of three or four mentors, who are early career researchers and emerging experts in the field. This setup enhances communication skills, encourages active involvement of the participants and forging new collaborations. Participants also cook, clean and eat together, further fostering the sense of community.<br/><br/>The planned topic for the 2025 Kylerec workshop is Floer homotopy theory, focusing on the emerging subject of lifting constructions in symplectic Floer theory to the level of stable homotopy theory, and applications to classical problems in symplectic geometry such as the classification of exact Lagrangian submanifolds or the study of Hamiltonian fibrations and families of symplectic manifolds. Ever since Floer's original breakthrough on the Arnold conjecture, constructions of Floer-type theories of increasing complexity were introduced with tremendous success for applications in symplectic topology, such as the recent Abouzaid–Blumberg result on the Arnold conjecture with mod p coefficients. The objective of the Kylerec workshop is to understand the current state of the art in these topics, including both the technical tools utilized and the applications, as well as some of the broader philosophy that has come out of the work on these topics. Along the way, we hope that participants will encounter a wide variety of different ideas coming from the various approaches, as well as exciting new areas and open problems stemming from the recent developments. Kylerec workshops website: https://kylerec.wordpress.com/<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/01/2024
|
08/01/2024
|
None
|
Grant
|
47.049
|
1
|
4900
|
4900
|
2430432
|
{'FirstName': 'Eleny-Nicoleta', 'LastName': 'Ionel', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Eleny-Nicoleta Ionel', 'EmailAddress': '[email protected]', 'NSF_ID': '000322137', 'StartDate': '08/01/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Stanford University', 'CityName': 'STANFORD', 'ZipCode': '943052004', 'PhoneNumber': '6507232300', 'StreetAddress': '450 JANE STANFORD WAY', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '16', 'CONGRESS_DISTRICT_ORG': 'CA16', 'ORG_UEI_NUM': 'HJD6G4D6TJY5', 'ORG_LGL_BUS_NAME': 'THE LELAND STANFORD JUNIOR UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Stanford University', 'CityName': 'STANFORD', 'StateCode': 'CA', 'ZipCode': '943052004', 'StreetAddress': '450 JANE STANFORD WAY', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '16', 'CONGRESS_DISTRICT_PERF': 'CA16'}
|
{'Code': '126700', 'Text': 'TOPOLOGY'}
|
2024~130483
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430432.xml'}
|
Collaborative Research: Stanford-Florida Program in Support of LIGO on Coatings and Core Optics
|
NSF
|
05/15/2024
|
05/31/2027
| 240,000 | 80,000 |
{'Value': 'Continuing Grant'}
|
{'Code': '03010000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'PHY', 'LongName': 'Division Of Physics'}}
|
{'SignBlockName': 'Pedro Marronetti', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927372'}
|
In 2015, scientists detected ripples in spacetime called gravitational waves, created by two black holes merging, which launched the field of gravitational-wave astronomy. Improvements in the sensitivity in the Advanced LIGO detectors made this revolution possible. Planned future upgrades to improve detector sensitivity will require reduced-thermal-noise mirror coatings that are used in the detector optics. These improvements will continue to impact gravitational-wave astronomy for at least 20 years. A planned upgrade called A-sharp aims to reduce the thermal noise from the mirror coatings by at least half. The challenge of developing lower thermal noise coatings requires progress in the understanding of the physics of amorphous oxide materials, which is the core research focus of this collaborative project. The collaboration brings together experts in both experimental and theoretical aspects of this research at Stanford University and the University of Florida. The goal is to create mirror coatings that meet the necessary standards for use in future LIGO detectors. The team will continue to train the next generation of STEM researchers and professionals through their multidisciplinary activities and outreach activities.<br/><br/>Future planned upgrades to LIGO will seek to install mirrors with further improved coatings, in particular with lower Brownian thermal noise (BTN), which is a key noise source limiting detector sensitivity. The baseline design for the potential A-sharp upgrade calls for a coating thermal noise reduced by a factor of at least two with respect to Advanced LIGO + (A+) levels. Synergies between the Stanford-Florida program and the Center for Coatings Research (CCR) have enabled considerable progress under previous support. Having identified, based on characterization via X-ray scattering and atomic structure modeling, the connection between room-temperature mechanical losses and edge- and face-shared polyhedral structural motifs, the team proposed Ti-doped GeO2 as a high refractive-index low-mechanical-loss coating. Subsequent experimental work in the CCR and LIGO Lab supported this identification, leading to the selection of this material for the A+ mirrors. The research conducted under this award builds on these results, with a goal of finding coating solutions with a further factor of two reduction in thermal noise for mirror upgrades and/or an A-sharp system. The group will work iteratively with deposition groups developing amorphous coatings, both refining the atomic structure models with data generated from the materials they deposit, and by providing those groups with guidance for next steps in their synthesis campaigns based on the results from the atomic structure and modeling efforts. While the major portion of our work will remain focused on amorphous coatings, the group will also continue to contribute to crystalline AlGaAs coatings by characterizing optical absorption and developing models for birefringence and observed excess noise above the expected Brownian contribution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
05/02/2024
|
05/02/2024
|
None
|
Grant
|
47.049
|
1
|
4900
|
4900
|
2430436
|
{'FirstName': 'Hai-Ping', 'LastName': 'Cheng', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Hai-Ping Cheng', 'EmailAddress': '[email protected]', 'NSF_ID': '000307254', 'StartDate': '05/02/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Northeastern University', 'CityName': 'BOSTON', 'ZipCode': '021155005', 'PhoneNumber': '6173733004', 'StreetAddress': '360 HUNTINGTON AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MA07', 'ORG_UEI_NUM': 'HLTMVS2JZBS6', 'ORG_LGL_BUS_NAME': 'NORTHEASTERN UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Northeastern University', 'CityName': 'BOSTON', 'StateCode': 'MA', 'ZipCode': '021155005', 'StreetAddress': '360 HUNTINGTON AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MA07'}
|
{'Code': '125200', 'Text': 'LIGO RESEARCH SUPPORT'}
|
2024~80000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430436.xml'}
|
WEPPE: Wireless Edge-Computing Personal Protective Equipment for Large-Scale Health Monitoring
|
NSF
|
02/01/2024
|
08/31/2025
| 499,574 | 373,566 |
{'Value': 'Standard Grant'}
|
{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}
|
{'SignBlockName': 'Huaiyu Dai', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924568'}
|
The research objective of this proposal is to provide a general-purpose, scalable edge-computing architecture critically needed to support the next generation of personal protective equipment (PPE) technology. The proliferation of sensors and wireless sensor networks (WSNs) results in high-volume data generation, increases the computational burden at the central data center, creates data transmission bottlenecks, and hinders the real-time decision-making process. These challenges arise due to the existing limits of IoT devices on computational power, memory, and wireless bandwidth (BW) allocation. The case study chosen as a framework for developing such a system is motivated by the recent and urgent need for better tracking of the spread of transmittable diseases over large areas. The WEPPE project will resort to two-phase approaches to address the challenges mentioned earlier. In the first phase, the project will investigate a low-cost inkjet-printable nonlinear-element and develop a machine-learning platform on a flexible substrate for low-level sensor data processing or in-situ computation. In the second phase, the project will integrate an efficient analog pulse-based data encoding and decoding scheme to wirelessly relay the processed sensor data from the first phase to a data center without requiring extended network bandwidth. The proposed WEPPE project is expected to produce a unique machine learning framework that hinges on the fundamentals of reservoir computing, novel inkjet-printed sensors and nonlinear elements, and wireless data telemetry scheme with secure communication. Customized hardware and low-level computing will enable in situ edge computing while maintaining quality data abstraction for real-time network-level or big data processing for rapid decision-making. The education goal is to broaden the participation of female, minority, and African-American students and train and educate them for the next era of engineering challenges.<br/><br/>This proposed project will investigate how edge computing via hardware-based machine learning and data encryption/decryption schemes may effectively resolve the IoT problems of limited bandwidth, secure data transmission, high-density data throughput, and power-efficient in-situ computation. The project has targeted mainly four research goals - (i) Research on Reservoir Computing Architectures for Sensor Network Analysis, (ii) Research on Inkjet-Printed Devices for Sensing and Physical Computing, (iii) Investigate Energy-Efficient Orthogonal Pulses and Multi-bit Data Mapping, and (iv) Research on Orthogonal Analog Pulse Based Data Compression and Decompression. A reservoir computing architecture-based machine learning platform, especially the Echo State Network (ESN), will be investigated for its simplicity, less training time with relatively reduced training data volume, and ease of deployment. As an integral part of this effort, the project will also investigate an inkjet-printed low-cost nonlinear element, which will be a core building block for developing a machine-learning platform on a flexible substrate. The reservoir will generate a state vector, which is a hyper-dimensionalized encrypted representation of the raw data, and as a result, will provide data compression and security. Fault detection and sensor fusion will occur by training the reservoir and merging the state vectors. The state vectors from the reservoirs will then be further encrypted and spectrally compressed in the "Wearable Hub" by a k-bit encoding scheme using analog orthogonal pulses (AOP). At the "Local Server," the encoded AOPs from all the wearable hubs will be compressed by an n-pulse compression technique and transmitted to the "Data Center." The secured receiver at the "Data Center" will decode the state vectors using secured read-out neurons, providing predictions to be sent back to the end users for monitoring or large-scale processing by deep learning and other machine learning methods.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
04/29/2024
|
04/29/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2430440
|
{'FirstName': 'Mohammad', 'LastName': 'Haider', 'PI_MID_INIT': 'R', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Mohammad R Haider', 'EmailAddress': '[email protected]', 'NSF_ID': '000623168', 'StartDate': '04/29/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Missouri-Columbia', 'CityName': 'COLUMBIA', 'ZipCode': '652113020', 'PhoneNumber': '5738827560', 'StreetAddress': '121 UNIVERSITY HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Missouri', 'StateCode': 'MO', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'MO03', 'ORG_UEI_NUM': 'SZPJL5ZRCLF4', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF MISSOURI SYSTEM', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Missouri-Columbia', 'CityName': 'COLUMBIA', 'StateCode': 'MO', 'ZipCode': '652113020', 'StreetAddress': '121 UNIVERSITY HALL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Missouri', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'MO03'}
|
{'Code': '756400', 'Text': 'CCSS-Comms Circuits & Sens Sys'}
|
2022~373566
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430440.xml'}
|
Travel: Student Travel Support for MVAPICH User Group (MUG) 2024 Conference
|
NSF
|
08/01/2024
|
07/31/2025
| 10,000 | 10,000 |
{'Value': 'Standard Grant'}
|
{'Code': '05090000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'OAC', 'LongName': 'Office of Advanced Cyberinfrastructure (OAC)'}}
|
{'SignBlockName': 'Sheikh Ghafoor', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927116'}
|
The 2024 MVAPICH User group (MUG) Conference is a gathering of experts, including users, system administrators, researchers, engineers, and students, focused on sharing knowledge about the MVAPICH libraries. It provides a platform for discussions and presentations from renowned researchers, users, and system administrators in the field. The event also features contributed presentations selected by the MVAPICH team, focusing on tuning, optimization strategies, troubleshooting guidelines, and more. Scheduled to take place in Columbus, OH, from August 19-21, 2024, the conference is organized by a distinguished group of specialists in message passing (MPI) and networking technologies. To support student participation, the project will provide funding, enabling them to engage with the MVAPICH research and user community. The conference serves the national interest by fostering research dissemination, facilitating connections among researchers, and training the next generation of scholars, aligned with the mission of the National Science Foundation (NSF). The organizers aim to recruit students from diverse institutions, emphasizing inclusivity. Attending the conference offers students various benefits, such as 1) exposure to cutting-edge high-performance computing (HPC) technologies, 2) in-depth understanding of designing open-source software environments for HPC systems, 3) training on optimization techniques, and 4) opportunities for interaction with industry professionals and national laboratory experts. The NSF funding significantly impacts the future careers of researchers in HPC, networking, and message passing technologies, while promoting diversity within the field.<br/><br/>This project supports the rapidly evolving landscape of Modern High-Performance Computing (HPC) systems and preparing the next generation of engineers and scientists to navigate these advancements. With the emergence of multi-/many-core platforms like Intel Xeons, AMD EPYC, NVIDIA Grace, ARM and OpenPOWER; and various GPUs (NVIDIA, AMD, and Intel), coupled with RDMA-enabled networking technologies such as InfiniBand, RoCE, iWARP, Omni-Path, and Slingshot 11, it is crucial to understand and utilize these technologies to design HPC software stacks. The MVAPICH open-source message passing interface (MPI) library and its derivatives have played a significant role in exploiting the potential of RDMA-capable networks, resulting in the rapid growth and adoption of InfiniBand in the HPC community. The popularity of MVAPICH is evident, with over 3,375 organizations worldwide (in 91 countries) utilizing these libraries, resulting in more than 1.78 million downloads from the OSU website as of May 2024. Moreover, the annual MVAPICH User Group conference provides a collaborative platform for users, researchers, administrators, and students to exchange knowledge, share experiences, and discuss optimization strategies, troubleshooting guidelines, and other relevant topics. This project not only advances the field of HPC but also supports education, promotes diversity, and benefits society at large.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
05/19/2024
|
05/19/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2430444
|
[{'FirstName': 'Dhabaleswar', 'LastName': 'Panda', 'PI_MID_INIT': 'K', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Dhabaleswar K Panda', 'EmailAddress': '[email protected]', 'NSF_ID': '000487085', 'StartDate': '05/19/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Hari', 'LastName': 'Subramoni', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Hari Subramoni', 'EmailAddress': '[email protected]', 'NSF_ID': '000704577', 'StartDate': '05/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Aamir', 'LastName': 'Shafi', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Aamir Shafi', 'EmailAddress': '[email protected]', 'NSF_ID': '000841500', 'StartDate': '05/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Mustafa', 'LastName': 'Abduljabbar', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Mustafa Abduljabbar', 'EmailAddress': '[email protected]', 'NSF_ID': '000931934', 'StartDate': '05/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Ohio State University', 'CityName': 'COLUMBUS', 'ZipCode': '432101016', 'PhoneNumber': '6146888735', 'StreetAddress': '1960 KENNY RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Ohio', 'StateCode': 'OH', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'OH03', 'ORG_UEI_NUM': 'DLWBSLWAJWR1', 'ORG_LGL_BUS_NAME': 'OHIO STATE UNIVERSITY, THE', 'ORG_PRNT_UEI_NUM': 'MN4MDDMN8529'}
|
{'Name': 'Ohio State University', 'CityName': 'COLUMBUS', 'StateCode': 'OH', 'ZipCode': '432101016', 'StreetAddress': '1960 KENNY RD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Ohio', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'OH03'}
|
{'Code': '800400', 'Text': 'Software Institutes'}
|
2024~10000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430444.xml'}
|
Conference: 2024 Granular Matter GRC and GRC Particle Systems Science and Extreme Environments
|
NSF
|
07/01/2024
|
06/30/2025
| 32,000 | 32,000 |
{'Value': 'Standard Grant'}
|
{'Code': '06030000', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'EAR', 'LongName': 'Division Of Earth Sciences'}}
|
{'SignBlockName': 'Justin Lawrence', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922425'}
|
This award supports scientists and engineers, those early in their career and from under-represented groups and non-R1 institutions, to attend the eleventh Gordon Research Conference (GRC) on Granular Matter to be held on June 21-26, 2024, at Stonehill College in Easton, MA. The award will also support early career scientists and engineers attending the associated Gordon Research Seminar (GRS) held during the two days before the GRC meeting at the same place. The goal of the 2024 GRC and GRS on Granular Matter is to significantly enhance the rate of progress in understanding granular materials in complex settings relevant to many disciplines. To do so, these meetings are designed to meet the following objectives: 1. Presentation and discussion of unpublished, novel findings from researchers of a wide range of backgrounds; 2. Cultivation and promotion of emerging junior researchers, particularly, those from underrepresented groups; 3. Provide opportunities for extended discussion periods and interaction among researchers of different disciplines, backgrounds, and professions whose paths do not normally overlap. This year’s invited sessions are cross populated by researchers with backgrounds in geoscience, physics, materials science, engineering, and applied mathematics. Various activities for diversifying the impact of the meeting are included, such as a career panel with participants from different sectors and a program on inclusion, equity, and professional development.<br/><br/>Granular matter, conglomerations of particles or of particles and fluids, is abundant in nature and industry, studied in multiple science and engineering disciplines. Much is now known about the dynamics of relatively simple particulate systems (e.g., narrow size distributions of spherical particles) at low solids concentrations, and inroads have been made into behaviors of denser systems. Yet, fundamental questions remain out of reach for more complex systems including: (1) angular/aspherical particles (2) widely dispersed in size and density, (3) interacting via complex forces (e.g., via interstitial fluids). To address these fundamental challenges requires efforts from scientists and engineers coordinated across research fields. The biannual GRC and GRS provide platforms for researchers to discuss and exchange recent developments in granular matter and unmet needs across disciplines. The meeting chairs and vice-chairs are experts in granular media at different career stages and work in complimentary disciplines. The meeting structure emphasizes presentations of new work, and discussion among researchers from disciplines that typically do not have intersecting platforms. The GRC/GRS provide time for: (1) formal discussion after every talk (guided by a discussion leader), (2) time in the afternoons for informal follow-on discussions and late afternoon poster sessions, and (3) shared meals, all of which maximize interactions between participants across backgrounds during the meeting.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
06/21/2024
|
06/21/2024
|
None
|
Grant
|
47.041, 47.049, 47.050
|
1
|
4900
|
4900
|
2430452
|
{'FirstName': 'Kimberly', 'LastName': 'Hill', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Kimberly M Hill', 'EmailAddress': '[email protected]', 'NSF_ID': '000152590', 'StartDate': '06/21/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Gordon Research Conferences', 'CityName': 'EAST GREENWICH', 'ZipCode': '028183454', 'PhoneNumber': '4017834011', 'StreetAddress': '5586 POST RD UNIT 2', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Rhode Island', 'StateCode': 'RI', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'RI02', 'ORG_UEI_NUM': 'XL5ANMKWN557', 'ORG_LGL_BUS_NAME': 'GORDON RESEARCH CONFERENCES', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Gordon Research Conferences', 'CityName': 'EAST GREENWICH', 'StateCode': 'RI', 'ZipCode': '028183454', 'StreetAddress': '5586 POST RD UNIT 2', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Rhode Island', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'RI02'}
|
[{'Code': '141500', 'Text': 'PMP-Particul&MultiphaseProcess'}, {'Code': '157400', 'Text': 'Geophysics'}, {'Code': '171000', 'Text': 'CONDENSED MATTER PHYSICS'}, {'Code': '745800', 'Text': 'Geomorphology & Land-use Dynam'}]
|
2024~32000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430452.xml'}
|
Fundamental behavior of heat and mass transfer in multicomponent mixtures featuring phase change materials in liquid metal suspensions and high vapor pressure fluids
|
NSF
|
08/01/2024
|
07/31/2027
| 499,232 | 499,232 |
{'Value': 'Standard Grant'}
|
{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}
|
{'SignBlockName': 'Sumanta Acharya', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924509'}
|
Many electronic and industrial systems require increasingly higher heat removal capacities to accommodate the escalating heat produced by the micro-miniaturization of electronic components. Phase change materials have been commonly employed for thermal management; for example, fluids changing phase from liquid-to-vapor, and/or combinations of multiple fluids that change phases to improve thermal transport. This work proposes to study the use of novel multicomponent fluid mixtures to augment and improve the heat transfer rates. Multicomponent fluid mixtures in this study consist of mixtures of multiple fluids, solid particles that change phase to liquid, and refrigerants that can vaporize. The principal aim of this project is to provide a deep understanding of interactions among multicomponent fluid mixtures through both experimentation and simulations. This can then be used to further enhance the performance of many different types of heat transfer systems. The project will include significant educational activities, including the creation of educational materials for undergraduate and graduate programs using the associated research outcomes. This material will be modified for high school and middle school students through the creation of tutorials and video lectures. <br/><br/>The investigation utilizes novel multicomponent fluid mixtures to augment internal convective and phase change heat transfer. The multicomponent fluid mixture refers to a novel mixture of multiple fluids and particles that includes phase change materials (PCMs), such as paraffin wax, suspended in liquid gallium alloys utilizing the stabilization properties of gallium oxide films around the suspended particles, in addition to a high vapor pressure refrigerant at saturation conditions. It is proposed that the gallium alloy properties can be improved by embedding PCM particles, such as paraffin wax that have a high heat capacity and low density. Further performance improvements are proposed through the deposition of a gallium oxide film on the channel wall, thereby increasing the wettability of the gallium alloy and consequently improving its mass transport. The proposed work will (i) develop a new understanding of the stability of various PCM particles/gallium alloy mixtures in a range of concentrations and the important properties of these mixtures; (ii) illuminate complex multi-fluid heat and mass transfer phenomena using liquid metals alongside high vapor pressure fluids; and (iii) illuminate the underlying mechanisms of the interactions in the multicomponent mixture. An Oscillating Heat Pipe (OHP) that is commonly used in thermal management applications will be studied with the proposed multicomponent mixture. The knowledge gained from this project has the potential to dramatically increase the efficiency of heat dissipation and transport in electronic and industrial systems.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/16/2024
|
08/16/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2430453
|
{'FirstName': 'Satish', 'LastName': 'Kumar', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Satish Kumar', 'EmailAddress': '[email protected]', 'NSF_ID': '000527324', 'StartDate': '08/16/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Georgia Tech Research Corporation', 'CityName': 'ATLANTA', 'ZipCode': '303186395', 'PhoneNumber': '4048944819', 'StreetAddress': '926 DALNEY ST NW', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Georgia', 'StateCode': 'GA', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'GA05', 'ORG_UEI_NUM': 'EMW9FC8J3HN4', 'ORG_LGL_BUS_NAME': 'GEORGIA TECH RESEARCH CORP', 'ORG_PRNT_UEI_NUM': 'EMW9FC8J3HN4'}
|
{'Name': 'Georgia Institute of Technology', 'CityName': 'Atlanta', 'StateCode': 'GA', 'ZipCode': '303320245', 'StreetAddress': '771 Ferst Drive', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Georgia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'GA05'}
|
{'Code': '164200', 'Text': 'Special Initiatives'}
|
2024~499232
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430453.xml'}
|
Access and Accessibility in STEM: An Organizational Route to Tenure Line Faculty Positions
|
NSF
|
11/01/2024
|
10/31/2027
| 1,249,664 | 1,249,664 |
{'Value': 'Standard Grant'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Eileen Parsons', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927135'}
|
This project intends to support three postdoctoral fellows focused on access and accessibility in science, technology, engineering and mathematics (STEM) education research, practice, and policy. Because issues of STEM access and accessibility are inherently transdisciplinary, with relevant challenges spanning contexts, disciplines, and populations, this program plans to work with postdoctoral researchers to develop depth and breadth of knowledge in their areas of interest. Project leadership intends to collaborate with both supervising faculty and the postdoctoral fellows in their engagement in ongoing projects as well as in their independent research. This collaboration is designed to serve as a sustaining partnership extending from postdoctoral training through subsequent careers as tenure-track faculty within the institution.<br/><br/>Postdoctoral research positions are invaluable opportunities for early career researchers to both establish themselves as independent scholars and to benefit from ongoing training. These roles also typically entail precarity, because they are designed to be temporary, may lack clear definitions of work responsibilities, and do not guarantee access to subsequent academic positions. However, the model of postdoctoral training proposed in this project is intended for early career scholars to transition directly into tenure line positions in the Emma Eccles Jones College of Education and Human Services (CEHS) at Utah State University, pending adequate performance. The training provided within this model fully immerses the postdoctoral fellows in a highly collaborative and supportive environment rich in opportunities for the development of independent scholarship and for engagement with existing projects of senior colleagues. The performance criteria that structure the goals of independent scholarship are the need to develop a grant proposal for a new project and to lead on at least two manuscripts in two years. The supports provided include mentorship networks and formal training in methodology, grant writing, and pedagogy. The supports also include funds in each year to cover the research costs of fellows, full access to both the statistics consulting studio and the grant development office which are staffed and fully funded by CEHS, and monthly collaborative cohort meetings. <br/><br/>This project is funded by the STEM Education Postdoctoral Research Fellowship Program (STEM Ed PRF) in partnership with the NSF Improving Undergraduate STEM Education (IUSE: EDU) Program. The STEM Ed PRF Program aims to enhance the research knowledge, skills, and practices of recent doctorates in STEM, STEM education, education, and related disciplines to advance their preparation to engage in fundamental and applied research that advances knowledge within the field. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/05/2024
|
08/05/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2430462
|
[{'FirstName': 'David', 'LastName': 'Feldon', 'PI_MID_INIT': 'F', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'David F Feldon', 'EmailAddress': '[email protected]', 'NSF_ID': '000470849', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Shawn', 'LastName': 'Whiteman', 'PI_MID_INIT': 'D', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Shawn D Whiteman', 'EmailAddress': '[email protected]', 'NSF_ID': '000932332', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Utah State University', 'CityName': 'LOGAN', 'ZipCode': '843221000', 'PhoneNumber': '4357971226', 'StreetAddress': '1000 OLD MAIN HL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Utah', 'StateCode': 'UT', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'UT01', 'ORG_UEI_NUM': 'SPE2YDWHDYU4', 'ORG_LGL_BUS_NAME': 'UTAH STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Utah State University', 'CityName': 'LOGAN', 'StateCode': 'UT', 'ZipCode': '843221000', 'StreetAddress': '1000 OLD MAIN HL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Utah', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'UT01'}
|
[{'Code': '199800', 'Text': 'IUSE'}, {'Code': '713700', 'Text': 'Postdoctoral Fellowships'}]
|
2024~1249664
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430462.xml'}
|
Authentic Community-Engaged Scholarship in STEM Education Postdoc Training Program
|
NSF
|
10/01/2024
|
09/30/2027
| 1,227,108 | 1,227,108 |
{'Value': 'Standard Grant'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Fengfeng Ke', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922411'}
|
Given the importance of developing a well-equipped United States STEM workforce, the number of STEM postdoctoral researchers has increased more than threefold over the past 40 years. However, inequalities related to power dynamics, race, gender, and the types of training postdoctoral researchers receive persist. While research training and publication have traditionally been the standard for STEM research training programs, these experiences often lack structured and formal community support, especially for postdoctoral fellows. Because many postdocs transition into future positions involving various degrees of teaching, research, and service to their local and connected communities, there is significance and importance to providing effective education and training in these areas. As such, the project team seeks to develop three independent STEM education researchers equipped with distinctive skills in building community-engaged research-practice partnerships. The project aims to train postdoctoral researchers through structured cohort-based training designed to enhance the six core competencies outlined by the National Postdoctoral Association as important for postdoctoral success. These core competencies include discipline-specific conceptual knowledge, professionalism, enhanced research skills, responsible conduct of research, communication skills, and leadership and management skills. The project team plans to recruit postdoctoral researchers from a large and diverse network of scholars through recruiting at academic conferences, virtual recruiting events, and through electronic databases. Recognizing that some applicants will have more tangible products as a function of the prestige or recognition of the attended institution, the project team plans to prioritize applicants’ purpose and focus as indicated within the cover letter and recommendations rather than solely the number of publications and academic pedigree.<br/><br/>To achieve the goals of this project, the project team plans to leverage existing collaborations between the project team and partners within and surrounding Houston’s Historic Third Ward to provide postdoctoral researchers with community-engaged research opportunities. The project design is grounded in theoretical and conceptual frameworks that facilitate learning by doing and acknowledges the assets-based cultural capital postdoctoral researchers both bring with them and apply within their research. The project team intends to implement immediate engagement in existing research projects led by the project team, weekly research and mentoring meetings, the opportunity to audit research methods courses of their choosing, and enrollment in the ProQual Institute of Interpretive Research Methods. The project also aims to implement a professional development plan that includes onboarding, creating an individualized development plan, monthly networking, immersive teaching and mentoring experiences, and participation in training on topics such as grant writing and academic writing. <br/><br/>This project is funded by the Science, technology, engineering, and mathematics (STEM) Education Postdoctoral Research Fellowship Program (STEM Ed PRF) with co-funding from the Advancing Informal STEM Learning (AISL) and EDU Core Research: Building Capacity in STEM Education Research (ECR: BCSER). The STEM Ed PRF Program aims to enhance the research knowledge, skills, and practices of recent doctorates in STEM, STEM education, education, and related disciplines to advance their preparation to engage in fundamental and applied research that advances knowledge within the field. The AISL Program, supports projects that: (a) contribute to research and practice that considers informal STEM learning's role in equity and belonging in STEM; (b) promote personal and educational success in STEM; (c) advance public engagement in scientific discovery; (d) foster interest in STEM careers; (e) create and enhance the theoretical and empirical foundations for effective informal STEM learning; (f) improve community vibrancy; and/or (g) enhance science communication and the public's engagement in and understanding of STEM and STEM processes. The ECR: BCSER Program is designed to build the capacity of individuals to carry out high-quality, fundamental STEM education research in STEM learning and learning environments, broadening participation in STEM fields, and STEM workforce development.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/05/2024
|
08/05/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2430463
|
[{'FirstName': 'Jerrod', 'LastName': 'Henderson', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jerrod A Henderson', 'EmailAddress': '[email protected]', 'NSF_ID': '000589980', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Mariam', 'LastName': 'Manuel', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Mariam Manuel', 'EmailAddress': '[email protected]', 'NSF_ID': '000754163', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'April', 'LastName': 'Peters-Hawkins', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'April Peters-Hawkins', 'EmailAddress': '[email protected]', 'NSF_ID': '000922855', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'David', 'LastName': 'Horton', 'PI_MID_INIT': None, 'PI_SUFX_NAME': 'Jr', 'PI_FULL_NAME': 'David Horton', 'EmailAddress': '[email protected]', 'NSF_ID': '000945717', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'University of Houston', 'CityName': 'HOUSTON', 'ZipCode': '772043067', 'PhoneNumber': '7137435773', 'StreetAddress': '4300 MARTIN LUTHER KING BLVD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Texas', 'StateCode': 'TX', 'CONGRESSDISTRICT': '18', 'CONGRESS_DISTRICT_ORG': 'TX18', 'ORG_UEI_NUM': 'QKWEF8XLMTT3', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF HOUSTON SYSTEM', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Houston', 'CityName': 'HOUSTON', 'StateCode': 'TX', 'ZipCode': '772043067', 'StreetAddress': '4300 MARTIN LUTHER KING BLVD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Texas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '18', 'CONGRESS_DISTRICT_PERF': 'TX18'}
|
[{'Code': '162Y00', 'Text': 'ECR:BCSER Capcity STEM Ed Rscr'}, {'Code': '713700', 'Text': 'Postdoctoral Fellowships'}, {'Code': '725900', 'Text': 'AISL'}]
|
2024~1227108
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430463.xml'}
|
Conference: 2024 CISE CSforAll Technical Support to Broaden Participation in Computing
|
NSF
|
07/15/2024
|
06/30/2025
| 79,500 | 79,500 |
{'Value': 'Standard Grant'}
|
{'Code': '05010000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CCF', 'LongName': 'Division of Computing and Communication Foundations'}}
|
{'SignBlockName': 'Allyson Kennedy', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928905'}
|
The NSF CSforAll Research Practice Partnership (RPP) program aims to provide all U.S. students with the opportunity to participate in computer science and computational thinking education in their schools at the preK-12 levels. STARS Computing Corps, a CISE Broadening Participation in Computing Alliance, in partnership with Trivium Consulting Group, will provide resources and technical support to potential Principle Investigators (PIs) in order to increase their interest and capacity for creating and submitting competitive CSforAll RPP strand grant proposals. By building connections and potential collaborations among researchers and practitioners in diverse regions with diverse backgrounds and experiences, the project has the potential to foster community and introduce new and future PIs to the broader research community. <br/><br/>The 2024 CISE CSforAll Technical Support workshops aim to increase the breadth of projects supported through the NSF CSforAll program. The goal will be realized through multi-layered outreach to researchers and/or practitioners whose past experiences, interests, and expertise make them qualified candidates to carry out successful CSforAll proposals; registration and assessment of participant project ideas, teams, and expertise; provision of diverse online workshops and sessions (that can be engaged in synchronously or asynchronously) in critical elements of successful proposal development; and one-on-one technical support in key proposal development activities.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/02/2024
|
07/02/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2430490
|
[{'FirstName': 'Anna', 'LastName': 'Suarez', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Anna Suarez', 'EmailAddress': '[email protected]', 'NSF_ID': '000676186', 'StartDate': '07/02/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Jamie', 'LastName': 'Payton', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jamie J Payton', 'EmailAddress': '[email protected]', 'NSF_ID': '000723533', 'StartDate': '07/02/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'Temple University', 'CityName': 'PHILADELPHIA', 'ZipCode': '191226104', 'PhoneNumber': '2157077547', 'StreetAddress': '1805 N BROAD ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'StateCode': 'PA', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'PA02', 'ORG_UEI_NUM': 'QD4MGHFDJKU1', 'ORG_LGL_BUS_NAME': 'TEMPLE UNIVERSITY-OF THE COMMONWEALTH SYSTEM OF HIGHER EDUCATION', 'ORG_PRNT_UEI_NUM': 'QD4MGHFDJKU1'}
|
{'Name': 'Temple University', 'CityName': 'PHILADELPHIA', 'StateCode': 'PA', 'ZipCode': '191226104', 'StreetAddress': '1805 N BROAD ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'PA02'}
|
{'Code': '055Y00', 'Text': 'CISE Education and Workforce'}
|
2024~79500
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430490.xml'}
|
NSF STEM Ed OPRF: The Cornell Interdisciplinary Education Research Postdoctoral Cohort
|
NSF
|
10/01/2024
|
09/30/2027
| 1,250,000 | 1,250,000 |
{'Value': 'Standard Grant'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Joyce Belcher', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928221'}
|
In this Science, Technology, Engineering, and Math (STEM) Education Organizational Postdoctoral Research Fellowship project, three postdocs will be recruited to join a vibrant Discipline-Based Education Research (DBER) community at Cornell University and develop as future leaders. This work will serve the national interest by promoting the progress of science through interdisciplinary and multi-institutional education research projects and by developing the Cornell Interdisciplinary Discipline-Based Education Research (CIDER) postdocs as future leaders in science education through a comprehensive professional development program that includes research mentoring and development, network building, leadership, teaching opportunities, and career planning. The CIDER program will nurture an inclusive, supportive, and diverse community of emerging scholars using a nested mentoring approach. By working together as a PI-team to engage in and refine CIDER's approach, there will be impacts on the postdoc mentoring system across Cornell DBER, which affects future scholars beyond the life of this grant. CIDER postdocs will also provide workshops to national audiences on developing DBER scholars and organize an Upstate New York DBER conference including faculty from community colleges, primarily undergraduate institutions, and PhD-granting institutions. The conference will provide a venue to share the range of research activities across the local community and include a collaborative session about designing and assessing the outcomes of DBER postdoc programs. These events strengthen the STEM education community more broadly and provide multiple ways to disseminate findings.<br/><br/>The CIDER postdoc program relies on a nested mentoring approach to provide mentoring, guidance, and support to the CIDER postdocs. This approach avoids a hierarchical, top-down mentoring relationship and instead embraces mentoring as a partnership among a constellation of mentors, postdocs, and their networks and resources. To support interdisciplinary research, the CIDER postdocs will each work with Cornell DBER research mentors from multiple disciplines to design and conduct research aligned with their interests and career goals, and leverage insights across DBER fields. To support work at multiple institutions, the research mentors will help CIDER postdocs form networks to conduct their research in multiple contexts. This approach will involve engaging connections the PI team has previously established, attending conferences together, inviting outside speakers to give seminars in multiple departments throughout Cornell, and hosting a regional conference with instructors and researchers from multiple institution types. The application of the postdocs’ research results will contribute to broadening participation in STEM and improving STEM education for students from multiple institution types and disciplines, both directly through the research activities and indirectly through dissemination. The intellectual merits also lie in the long-term research activities of the CIDER postdocs as a result of the professional development opportunities afforded through this program.<br/><br/>This project is funded by the Science, Technology, Engineering, and Mathematics (STEM) Education Postdoctoral Research Fellowship Program (STEM Ed PRF) with co-funding from the Improving Undergraduate STEM Education Program (IUSE:EDU) and the EDU Core Research: Building Capacity in STEM Education Research (ECR:BCSER) Program. The STEM Ed PRF Program aims to enhance the research knowledge, skills, and practices of recent doctorates in STEM, STEM education, education, and related disciplines to advance their preparation to engage in fundamental and applied research that advances knowledge within the field. The NSF IUSE:EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. ECR: BCSER is designed to build the capacity of individuals to carry out high-quality, fundamental STEM education research in STEM learning and learning environments, broadening participation in STEM fields, and STEM workforce development.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/05/2024
|
08/05/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2430496
|
[{'FirstName': 'Michelle', 'LastName': 'Smith', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Michelle Smith', 'EmailAddress': '[email protected]', 'NSF_ID': '000608105', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Allison', 'LastName': 'Godwin', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Allison Godwin', 'EmailAddress': '[email protected]', 'NSF_ID': '000677512', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Natasha', 'LastName': 'Holmes', 'PI_MID_INIT': 'G', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Natasha G Holmes', 'EmailAddress': '[email protected]', 'NSF_ID': '000728964', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Alexandra', 'LastName': 'Werth', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Alexandra Werth', 'EmailAddress': '[email protected]', 'NSF_ID': '000966411', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Cornell University', 'CityName': 'ITHACA', 'ZipCode': '148502820', 'PhoneNumber': '6072555014', 'StreetAddress': '341 PINE TREE RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '19', 'CONGRESS_DISTRICT_ORG': 'NY19', 'ORG_UEI_NUM': 'G56PUALJ3KT5', 'ORG_LGL_BUS_NAME': 'CORNELL UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Cornell University', 'CityName': 'ITHACA', 'StateCode': 'NY', 'ZipCode': '148502820', 'StreetAddress': '341 PINE TREE RD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '19', 'CONGRESS_DISTRICT_PERF': 'NY19'}
|
[{'Code': '162Y00', 'Text': 'ECR:BCSER Capcity STEM Ed Rscr'}, {'Code': '199800', 'Text': 'IUSE'}, {'Code': '713700', 'Text': 'Postdoctoral Fellowships'}]
|
2024~1250000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430496.xml'}
|
Communication, Collaboration, Coordination: Preparing Postdoctoral Fellows to be Embedded in Engineering Disciplines
|
NSF
|
11/01/2024
|
10/31/2027
| 1,208,862 | 1,208,862 |
{'Value': 'Standard Grant'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Andrea Nixon', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922321'}
|
Engineering education (EER) PhD graduates are increasingly being hired into education research faculty positions in technical engineering departments. These positions present multiple challenges for new EER graduates. One particular challenge is lack of experience with navigating the cultural and expertise differences between engineering education and the technical engineering disciplines. The proposed project is designed to develop three postdoctoral fellows' capacity to span these disciplinary boundaries so that they can solve complex education problems in engineering. While engaging in engineering education research, fellows will grow their "3Cs" boundary spanning competencies of communication, collaboration, and coordination. Ultimately, the outcomes of this postdoctoral program have the potential to inform similar postdoctoral programs, providing invaluable postdoctoral training experiences for future STEM education researchers.<br/><br/>The overall aim of this postdoctoral fellowships program is to prepare discipline-based education research (DBER) scholars for independent research within engineering (E) disciplines. DBER-E boundary spanners are individuals who can work across the knowledge and skills gap between those trained in engineering education and those with technical engineering backgrounds. Those trained to be boundary spanners in engineering education research will be uniquely positioned to facilitate collaboration among engineers, educators, and social scientists. The merit of this work is threefold. First, the program is designed to enable three scholars to create their own new, independent DBER-E programs by providing support and resources to engage in both education- and engineering-centered spaces, as they may experience in their future home engineering departments. Second, the fellows have strong potential to contribute to the research areas associated with the DBER-E program at the University of Nebraska at Lincoln that focus on student success and workforce preparation. Third, the program will examine the use of boundary spanning as a means of grounding postdoctoral training, with new materials and strategies for such programs. By integrating boundary spanning theory into postdoctoral development, there is the potential to generate new strategies for fostering collaboration across disciplines, enhancing and accelerating educational research, and advancing the overall quality of engineering education.<br/><br/>This project is funded by the Science, Technology, Engineering, and Mathematics (STEM) Education Postdoctoral Research Fellowship Program (STEM Ed PRF) with co-funding from the Improving Undergraduate STEM Education Program (IUSE:EDU) Program. The STEM Ed PRF Program aims to enhance the research knowledge, skills, and practices of recent doctorates in STEM, STEM education, education, and related disciplines to advance their preparation to engage in fundamental and applied research that advances knowledge within the field. The IUSE:EDU Program supports research and development projects to improve the effectiveness of STEM education for all students.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/05/2024
|
08/05/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2430498
|
[{'FirstName': 'Heidi', 'LastName': 'Diefes-Dux', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Heidi A Diefes-Dux', 'EmailAddress': '[email protected]', 'NSF_ID': '000177913', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Grace', 'LastName': 'Panther', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Grace Panther', 'EmailAddress': '[email protected]', 'NSF_ID': '000784721', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Logan', 'LastName': 'Perry', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Logan A Perry', 'EmailAddress': '[email protected]', 'NSF_ID': '000859577', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Jessica', 'LastName': 'Deters', 'PI_MID_INIT': 'R', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jessica R Deters', 'EmailAddress': '[email protected]', 'NSF_ID': '000888004', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'University of Nebraska-Lincoln', 'CityName': 'LINCOLN', 'ZipCode': '685032427', 'PhoneNumber': '4024723171', 'StreetAddress': '2200 VINE ST # 830861', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Nebraska', 'StateCode': 'NE', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'NE01', 'ORG_UEI_NUM': 'HTQ6K6NJFHA6', 'ORG_LGL_BUS_NAME': 'BOARD OF REGENTS OF THE UNIVERSITY OF NEBRASKA', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Nebraska-Lincoln', 'CityName': 'LINCOLN', 'StateCode': 'NE', 'ZipCode': '685830861', 'StreetAddress': '2200 VINE ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Nebraska', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'NE01'}
|
[{'Code': '199800', 'Text': 'IUSE'}, {'Code': '713700', 'Text': 'Postdoctoral Fellowships'}]
|
2024~1208862
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430498.xml'}
|
Travel: NSF Student Travel Grant for The 2024 IEEE International Workshop on LLM-Aided Design (LAD'24)
|
NSF
|
08/01/2024
|
07/31/2025
| 10,000 | 10,000 |
{'Value': 'Standard Grant'}
|
{'Code': '05010000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CCF', 'LongName': 'Division of Computing and Communication Foundations'}}
|
{'SignBlockName': 'Hu, X. Sharon', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928910'}
|
Recent strides in artificial intelligence (AI) have demonstrated impressive capabilities in assisting with a wide range of text-generation tasks. One promising use-case is the use generative AI methods to assist in developing software and hardware. Large Language Models (LLMs) are already in use to assist in software code generation, and recent research has demonstrated promise of LLMs in assisting in various stages of computer chip design. To further explore and encourage research in this rapidly advancing field, the inaugural International Symposium on LLM-Aided Design (LAD’24) seeks to bring together leading researchers from academia, industry and government and create a research community around this field. Graduate and undergraduate student researchers will be a critical part of this community, and this award will support travel for students with limited or no financial support to travel to LAD’24 in Almaden California.<br/><br/>Large Language Models (LLMs) are making significant strides in text and content generation for a wide range of tasks, and are proving to be helpful in developing software/hardware computing stacks. These advancements are poised to transform software and hardware code generation, system-level architecture design, electronic design automation flow, and test and verification processes. LAD’24 will capitalize on recent generative AI and LLM technology innovations, introducing new methods and solutions for design automation across various applications. It aims to establish itself as a leading forum for discussing how LLMs can enhance quality, productivity, robustness, and cost-efficiency in circuit, software, and computing systems design. This award will support up to ten graduate student researchers to attend LAD’24, allowing them to share their research and findings with academic and industry leaders in this nascent field.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/16/2024
|
07/16/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2430503
|
{'FirstName': 'Siddharth', 'LastName': 'Garg', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Siddharth Garg', 'EmailAddress': '[email protected]', 'NSF_ID': '000680915', 'StartDate': '07/16/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'New York University', 'CityName': 'NEW YORK', 'ZipCode': '100121019', 'PhoneNumber': '2129982121', 'StreetAddress': '70 WASHINGTON SQ S', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_ORG': 'NY10', 'ORG_UEI_NUM': 'NX9PXMKW5KW8', 'ORG_LGL_BUS_NAME': 'NEW YORK UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'New York University', 'CityName': 'NEW YORK', 'StateCode': 'NY', 'ZipCode': '100121019', 'StreetAddress': '70 WASHINGTON SQ S', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_PERF': 'NY10'}
|
{'Code': '779800', 'Text': 'Software & Hardware Foundation'}
|
2024~10000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430503.xml'}
|
NSF-SNSF:Learning disentangled graph representations for biomedicine
|
NSF
|
01/01/2025
|
12/31/2027
| 400,000 | 400,000 |
{'Value': 'Standard Grant'}
|
{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}
|
{'SignBlockName': 'Huaiyu Dai', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924568'}
|
With the recent advances in multimodal data acquisition technologies in healthcare, diverse and large volumes of biological omics, imaging and physiological data are collected at an exponentially increasing rate. The availability of this vast amount of data has allowed us to expand our understanding of physiological and pathological processes, enabling the development of novel healthcare solutions. However, this abundance of data also presents major challenges in analysis due to its complexity and volume. Complex networks (graphs) such as gene regulatory networks (GRNs) and functional connectivity networks (FCNs) of the brain have emerged as valuable tools for describing the interactions between biological targets, providing effective analytical frameworks to characterize the inherent complexities of biological data. Aspiring to address these challenges, this project introduces a comprehensive disentangled graph representation learning framework tailored to address the complexities of graph structured data commonly encountered in biomedical applications. Disentangled graph representation learning will benefit a gamut of research areas, including multimodal machine learning, social analytics, biology, health informatics, and infrastructure systems. In particular, it will have an impact in life science and medicine, where large volumes of unpaired data from various domains are common. Disentangling shared and distinct representations across domains can uncover associations between modalities and disease characteristics, refine patient stratification, and ultimately improve treatments by tailoring therapies to each subgroup more effectively. In addition to research, the project will impact the education and training of the next generation engineers and data scientists at all levels at both MSU and EPFL. <br/><br/>The goal of this project is to use principles of disentangled learning to incorporate insights from various domains and modalities and to extract shared and unique representations across different views, such as patients or data modalities. The proposed research is centered around four intertwined thrusts that broadly aim at: (T1) Structured Disentangled Multi-View Graph Inference; (T2) Multi-view Disentangled Graph Representation Learning; (T3) Multimodal Disentangled Learning and (T4) Application to biomedical data. The first thrust will develop a structured disentangled graph learning framework to infer both common and individual graph structures across multi-view datasets from observed data. The second thrust will move from dealing with unknown data domain to handling data across multiple known domains, represented as different layers in the same graph. Various interactions within biological data will be integrated using a multiplex graph representation learning framework. The third thrust will expand upon the framework developed in Thrust 2 by incorporating heterogeneous data from various modalities, including clinical, imaging, and genomic data. Finally, Thrust 4 will apply these methodological advancements to data from two domains: brain connectomics and cancer biology. Both disease and individual level representations will be learned for ultimately paving the way for precision medicine.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/13/2024
|
08/13/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2430516
|
{'FirstName': 'Selin', 'LastName': 'Aviyente', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Selin Aviyente', 'EmailAddress': '[email protected]', 'NSF_ID': '000326317', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Michigan State University', 'CityName': 'EAST LANSING', 'ZipCode': '488242600', 'PhoneNumber': '5173555040', 'StreetAddress': '426 AUDITORIUM RD RM 2', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Michigan', 'StateCode': 'MI', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MI07', 'ORG_UEI_NUM': 'R28EKN92ZTZ9', 'ORG_LGL_BUS_NAME': 'MICHIGAN STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'VJKZC4D1JN36'}
|
{'Name': 'Michigan State University', 'CityName': 'EAST LANSING', 'StateCode': 'MI', 'ZipCode': '488242600', 'StreetAddress': '426 AUDITORIUM RD RM 2', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Michigan', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MI07'}
|
{'Code': '756400', 'Text': 'CCSS-Comms Circuits & Sens Sys'}
|
2024~400000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430516.xml'}
|
George Mason University Quantum Education Research Postdoctoral Fellowship
|
NSF
|
01/01/2025
|
12/31/2027
| 1,246,608 | 1,246,608 |
{'Value': 'Standard Grant'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Andrea Nixon', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922321'}
|
Quantum information science is a transdisciplinary field spanning physics, math, chemistry, computer science, and most of the engineering disciplines. It involves the study of matter at the smallest scales -- the scale of atoms and subatomic particles -- and its application to a variety of technologies. Technologies based on quantum science are poised to revolutionize many aspects of our current world and industry predicts a need for a rapidly expanding quantum workforce. With the field poised for rapid growth, now is the time to understand and address systemic equity challenges in the field in order to build an inclusive and equitable workforce. Systemic challenges in quantum education and workforce development restrict access to key education and career opportunities, limiting the ability of institutions to meet industry needs. Researchers studying quantum education and workforce development can play key roles in understanding and addressing these challenges.<br/> <br/>The Quantum Education Research Postdoctoral Fellowship will prepare recent doctoral recipients to become leaders in quantum education and workforce development research. The program is designed to 1) launch the careers and individual research programs of three recent doctoral recipients with diverse personal, disciplinary, and research backgrounds; (2) support the use of a convergence approach to quantum education and workforce development research through a cohort research model that contributes to the establishment of a diverse and equitable quantum workforce; and (3) advance access, justice, equity, diversity and inclusion in STEM education through transdisciplinary research projects. The project aims to advance knowledge and understanding of systemic challenges to equity, inclusion, and access. Through this work, the Fellows can generate knowledge that can help in the creation of an inclusive and equitable workforce. The program will provide wrap-around support in the form of career guidance, mentorship, professional development workshops, and access to leaders in related disciplines to aid in Fellows’ development as leaders in this field.<br/><br/>This project is funded by the Science, technology, engineering, and mathematics (STEM) Education Postdoctoral Research Fellowship Program (STEM Ed PRF) with co-funding from the EDU Core Research: Building Capacity in STEM Education Research (ECR: BCSER) Program. The STEM Ed PRF Program aims to enhance the research knowledge, skills, and practices of recent doctorates in STEM, STEM education, education, and related disciplines to advance their preparation to engage in fundamental and applied research that advances knowledge within the field. ECR: BCSER is designed to build the capacity of individuals to carry out high-quality, fundamental STEM education research in STEM learning and learning environments, broadening participation in STEM fields, and STEM workforce development.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/14/2024
|
08/14/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2430519
|
[{'FirstName': 'Jessica', 'LastName': 'Rosenberg', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jessica Rosenberg', 'EmailAddress': '[email protected]', 'NSF_ID': '000167932', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Jill', 'LastName': 'Nelson', 'PI_MID_INIT': 'K', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jill K Nelson', 'EmailAddress': '[email protected]', 'NSF_ID': '000362592', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Nancy', 'LastName': 'Holincheck', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Nancy Holincheck', 'EmailAddress': '[email protected]', 'NSF_ID': '000709678', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Paula', 'LastName': 'Danquah-Brobby', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Paula Danquah-Brobby', 'EmailAddress': '[email protected]', 'NSF_ID': '000933077', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'George Mason University', 'CityName': 'FAIRFAX', 'ZipCode': '220304422', 'PhoneNumber': '7039932295', 'StreetAddress': '4400 UNIVERSITY DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Virginia', 'StateCode': 'VA', 'CONGRESSDISTRICT': '11', 'CONGRESS_DISTRICT_ORG': 'VA11', 'ORG_UEI_NUM': 'EADLFP7Z72E5', 'ORG_LGL_BUS_NAME': 'GEORGE MASON UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'H4NRWLFCDF43'}
|
{'Name': 'George Mason University', 'CityName': 'FAIRFAX', 'StateCode': 'VA', 'ZipCode': '220304422', 'StreetAddress': '4400 UNIVERSITY DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Virginia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '11', 'CONGRESS_DISTRICT_PERF': 'VA11'}
|
[{'Code': '162Y00', 'Text': 'ECR:BCSER Capcity STEM Ed Rscr'}, {'Code': '713700', 'Text': 'Postdoctoral Fellowships'}]
|
2024~1246608
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430519.xml'}
|
Teaching and Inclusion for Disability Equity in STEM: Postdoctoral Mentoring and Professional Development for Diverse Learning Environments
|
NSF
|
10/01/2024
|
09/30/2027
| 1,246,137 | 1,246,137 |
{'Value': 'Standard Grant'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Eileen Parsons', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927135'}
|
Existing graduate training models in STEM, STEM education, education, and related disciplines often artificially separate the study of inclusive education for disabled students from the study of highly effective teaching practices in STEM learning environments. The project aims to support the full inclusion of disabled students in STEM by recruiting and training a cohort of three postdoctoral scholars to pursue fundamental intersectional research on the science of broadening participation in STEM as it pertains to disability and ableism. It is anticipated each postdoctoral fellow will participate in a mentoring triad that includes two established scholars: one whose work focuses primarily on questions of STEM teaching and learning and one whose work focuses primarily on questions related to the full inclusion of disabled learners. The project is designed to build on the existing strengths of the University of Maine by leveraging the resources and ongoing research projects of the Maine Center for Research in STEM Education (RiSE Center), the College of Education and Human Development, and the Center for Community Inclusion and Disability Studies. The RiSE Center will facilitate access for postdoctoral fellows to the Maine STEM Partnership, a statewide preK–16+ STEM education improvement community. One project aim is to develop, implement, and evaluate a postdoctoral researcher training model focused on intersectionality and corresponding interventions in the context of disabled student experiences in STEM.<br/><br/>The fundamental innovation of the proposed postdoctoral training model is to prepare doctoral qualified researchers, including disabled researchers, to think about disability intersectionally and to design systematic interventions based on the science of broadening participation to support the full inclusion of multiply-minoritized disabled learners in STEM. The individual participation of each fellow in a mentoring triad is intended to provide a foundation for their participation in two research projects: 1) a new independent research project and 2) an existing team science project focused on the science of broadening participation for disabled and other minoritized learners. Equally important, the postdoctoral program is designed for fellows to participate in cohort-based professional development activities including workshops, short-duration training courses, and journal clubs. The purpose of these activities is to expose postdoctoral fellows to cutting-edge scholarship on intersectional approaches to the science of broadening participation and the full inclusion of disabled learners in STEM. The proposed project is developed to prepare the next generation of STEM leaders to work at the leading edge of theory, methods, and empirical insights to advance the science of broadening participation for disabled and multiply-minoritized STEM students.<br/><br/>This project is funded by the Science, technology, engineering, and mathematics (STEM) Education Postdoctoral Research Fellowship Program (STEM Ed PRF) with co-funding from Discovery Research PreK-12 (DRK-12) and EDU Core Research: Building Capacity in STEM Education Research (ECR: BCSER). The STEM Ed PRF Program aims to enhance the research knowledge, skills, and practices of recent doctorates in STEM, STEM education, education, and related disciplines to advance their preparation to engage in fundamental and applied research that advances knowledge within the field. The DRK-12 program seeks to significantly enhance the learning and teaching of STEM by preK-12 students and teachers, through research and development of innovative resources, models and tools. Projects in the DRK-12 program build on fundamental research in STEM education and prior research and development efforts that provide theoretical and empirical justification for proposed projects. ECR: BCSER is designed to build the capacity of individuals to carry out high-quality, fundamental STEM education research in STEM learning and learning environments, broadening participation in STEM fields, and STEM workforce development.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/05/2024
|
08/05/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2430520
|
[{'FirstName': 'Susan', 'LastName': 'McKay', 'PI_MID_INIT': 'R', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Susan R McKay', 'EmailAddress': '[email protected]', 'NSF_ID': '000191594', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Sara', 'LastName': 'Flanagan', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Sara Flanagan', 'EmailAddress': '[email protected]', 'NSF_ID': '000662415', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Ezekiel', 'LastName': 'Kimball', 'PI_MID_INIT': 'W', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ezekiel W Kimball', 'EmailAddress': '[email protected]', 'NSF_ID': '000690653', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Justin', 'LastName': 'Dimmel', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Justin Dimmel', 'EmailAddress': '[email protected]', 'NSF_ID': '000747931', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'University of Maine', 'CityName': 'ORONO', 'ZipCode': '044695717', 'PhoneNumber': '2075811484', 'StreetAddress': '5717 CORBETT HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Maine', 'StateCode': 'ME', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'ME02', 'ORG_UEI_NUM': 'PB3AJE5ZEJ59', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF MAINE SYSTEM', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Maine', 'CityName': 'ORONO', 'StateCode': 'ME', 'ZipCode': '044695717', 'StreetAddress': '5717 CORBETT HALL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Maine', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'ME02'}
|
[{'Code': '162Y00', 'Text': 'ECR:BCSER Capcity STEM Ed Rscr'}, {'Code': '713700', 'Text': 'Postdoctoral Fellowships'}, {'Code': '764500', 'Text': 'Discovery Research K-12'}]
|
2024~1246137
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430520.xml'}
|
The Berkeley Data Science Education Fellowship: Exploring Ethical and Inclusive Approaches to Data Science in a Shifting Landscape
|
NSF
|
10/01/2024
|
09/30/2027
| 1,245,903 | 1,245,903 |
{'Value': 'Standard Grant'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Joyce Belcher', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928221'}
|
This project will support a cohort of three postdoctoral fellows for two years as they study Data Science Education at The University of California, Berkeley and partner educational institutions. The College of Computing, Data Science, and Society houses a variety of curricular and educational initiatives that offer many opportunities to study pedagogy, educational trajectories, and ethics and inclusion in Data Science. Fellows will be recruited from diverse institution types and disciplinary backgrounds to conduct research on Data Science Education through first apprenticing with multiple research and curriculum development projects, and then designing their own independent research project with support from a mentorship team. Fellows will develop expertise in generating high-quality Data Science Education research and curriculum by working with educators across precollege, 2-year, and 4-year contexts; addressing equity and inclusion in Data Science Education spaces; and examining curriculum and instruction focused on teaching computing and data science to diverse audiences.<br/><br/>The rise of data-rich computing has had rippling effects across educational sectors. Since computing and data science are highly contextual and have clear social applications and social impacts, many have argued that they can serve as an integrative thread for diversifying Science, Technology, Engineering, and Mathematics broadly. However, a lack of academic preparation, and of curricular and instructional support, can present roadblocks especially for marginalized populations to enter the field. Despite these challenges, most empirical work in Data Science Education has focused on the design and evaluation of courses or major programs of study, rather than these deeper systemic issues related to student preparation, learning and retention. The Berkeley Data Science Education Fellowship will support training and research toward a coherent, interdisciplinary, mixed-methods approach to studying Data Science Education at a system level. The Fellowship will prepare three postdoctoral researchers to conduct high-quality social sciences research in complex contexts, in collaboration with interdisciplinary colleagues including domain experts and educators. In Year 1, Fellows will be provided broad exposure to Data Science curricular and educational initiatives as research apprentices with research projects that employ different methodologies and work with different student audiences. In Year 2, Fellows will commit to a specific project to complete a longer-term research internship, as well as designing and enacting an independent research project. Fellows will also participate in monthly community-building events and colloquia, teach Data Science workshops and/or courses, and receive professional development feedback and advice from a cadre of interdisciplinary mentors. Through these research and teaching experiences, Fellows will gain comfort and competency in research and development of large-scale, introductory technical Data Science courses and workshops, with an eye toward social and cultural relevance.<br/><br/>This project is funded by the Science, Technology, Engineering, and Mathematics (STEM) Education Postdoctoral Research Fellowship Program (STEM Ed PRF) with co-funding from the Improving Undergraduate STEM Education Program (IUSE:EDU) Program. The STEM Ed PRF Program aims to enhance the research knowledge, skills, and practices of recent doctorates in STEM, STEM education, education, and related disciplines to advance their preparation to engage in fundamental and applied research that advances knowledge within the field. The NSF IUSE:EDU Program supports research and development projects to improve the effectiveness of STEM education for all students.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/05/2024
|
08/05/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2430522
|
[{'FirstName': 'Michelle', 'LastName': 'Wilkerson', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Michelle Wilkerson', 'EmailAddress': '[email protected]', 'NSF_ID': '000604960', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Zachary', 'LastName': 'Pardos', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Zachary A Pardos', 'EmailAddress': '[email protected]', 'NSF_ID': '000651352', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Lisa', 'LastName': 'Yan', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Lisa Yan', 'EmailAddress': '[email protected]', 'NSF_ID': '000864701', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Claudia', 'LastName': 'von Vacano', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Claudia von Vacano', 'EmailAddress': '[email protected]', 'NSF_ID': '000956613', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'University of California-Berkeley', 'CityName': 'BERKELEY', 'ZipCode': '947101749', 'PhoneNumber': '5106433891', 'StreetAddress': '1608 4TH ST STE 201', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'CA12', 'ORG_UEI_NUM': 'GS3YEVSS12N6', 'ORG_LGL_BUS_NAME': 'REGENTS OF THE UNIVERSITY OF CALIFORNIA, THE', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of California-Berkeley', 'CityName': 'BERKELEY', 'StateCode': 'CA', 'ZipCode': '947101749', 'StreetAddress': '1608 Fourth Street, Suite 220', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'CA12'}
|
[{'Code': '199800', 'Text': 'IUSE'}, {'Code': '713700', 'Text': 'Postdoctoral Fellowships'}]
|
2024~1245903
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430522.xml'}
|
III: Small: Foundations of Trustworthy Deep Learning: Interpretable Neural Network models with Robustness Guarantees
|
NSF
|
09/01/2024
|
08/31/2027
| 596,797 | 596,797 |
{'Value': 'Standard Grant'}
|
{'Code': '05020000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'IIS', 'LongName': 'Div Of Information & Intelligent Systems'}}
|
{'SignBlockName': 'Sylvia Spengler', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927347'}
|
Deep neural networks have achieved remarkable success in fields ranging from computer vision to healthcare and autonomous driving. However, their susceptibility to various failure modes and blindspots can pose significant risks, especially in safety-critical and high-stakes applications. Given their complex and opaque “black-box” nature, understanding why and when deep neural networks fail is crucial for their safe real-world deployment. Existing mainstream interpretability methods for neural networks are limited—they focus mainly on subjective explanations based on influential features, fail to scale or explain the internal network processes, and struggle with minor input changes, which can be risky in high-stakes applications. This project aims to develop an automated framework for interpreting neural networks and to design robust, neural network models based on human-understandable concepts. These advancements will promote automation and scalability, ensure transparent decision-making, facilitate efficient model debugging, and enable timely intervention, leading to safer, more reliable, and widely trusted applications of deep learning technology in critical domains. <br/><br/>This project will develop methods that can be used to ensure modern deep neural network models are interpretable and trustworthy. It includes methods for (1) automating interpretations that describe the internal functioning of a deep neural network via human-understandable concepts without the need to collect curated and expert annotations; (2) learning intrinsically interpretable models that contain task-relevant human-interpretable concepts by design; (3) quantifying and ensuring the robustness and reliability of the generated interpretations and the neural network models. The methods will draw on the investigator’s expertise in trustworthy machine learning and neural network robustness verification techniques to develop scalable and automated methods that will promote interpretability, robustness, transparency, and reliability in deep learning. If successful, this project will guide the design of deep learning systems to guarantee transparency and robustness, and provide the tools needed to enforce these properties during model development and deployment.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/22/2024
|
08/22/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2430539
|
{'FirstName': 'Tsui-Wei', 'LastName': 'Weng', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Tsui-Wei Weng', 'EmailAddress': '[email protected]', 'NSF_ID': '000842499', 'StartDate': '08/22/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of California-San Diego', 'CityName': 'LA JOLLA', 'ZipCode': '920930021', 'PhoneNumber': '8585344896', 'StreetAddress': '9500 GILMAN DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '50', 'CONGRESS_DISTRICT_ORG': 'CA50', 'ORG_UEI_NUM': 'UYTTZT6G9DT1', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CALIFORNIA, SAN DIEGO', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of California-San Diego', 'CityName': 'LA JOLLA', 'StateCode': 'CA', 'ZipCode': '920930021', 'StreetAddress': '9500 GILMAN DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '50', 'CONGRESS_DISTRICT_PERF': 'CA50'}
|
{'Code': '736400', 'Text': 'Info Integration & Informatics'}
|
2024~596797
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430539.xml'}
|
Modeling for Understanding Physical Phenomena and Engaging Pre-Service Teachers in Science
|
NSF
|
04/01/2024
|
09/30/2025
| 299,939 | 275,626 |
{'Value': 'Standard Grant'}
|
{'Code': '11040000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DUE', 'LongName': 'Division Of Undergraduate Education'}}
|
{'SignBlockName': 'Jennifer Ellis', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922125'}
|
This project aims to serve the national interest by preparing elementary school teachers to integrate model-based inquiry into the curriculum to enhance student learning of science. In elementary schools, science is often taught utilizing English language arts best practices. Children read about and memorize science facts instead of engaging in science practices to develop scientific knowledge. In efforts to build prospective elementary science teacher understanding of, ability to, and preparedness for teaching using model-based inquiry (MBI) the project aims to situate MBI into a physical science course. The Modeling for Understanding Physical Phenomena and Engaging Teachers in Science (MUPPETS) project will develop a physical science course for prospective elementary teachers (to be taken prior to the science education methods course) in which the preservice teachers are learners of science in an environment that utilizes science education research-based pedagogical approaches. Pre-service teacher gain experience learning science using techniques well suited for elementary students and in accordance with the Next Generation Science Standards. When prospective elementary teachers enter the science education methods course, the physical science course experience is a familiar context to draw upon, an opportunity not typically found in elementary education teacher preparation programs.<br/><br/>The purpose of the MUPPETS project is to determine how prospective elementary teachers engage with model-based inquiry (MBI) that centers on gathering and making sense of data and peer-to-peer discourse. More specifically, this project seeks to understand how making sense of phenomena through collaborative discussions influences the composition and substance of models and explanations across model iterations to establish the impact on their understanding of (1) physical science, science, and universal epistemological views; (2) meta-modeling knowledge; and (3) modeling practice. Data is analyzed using a mixed-methods approach employing a quantitative analysis of pre-and post-survey data to assess prospective elementary teachers’ views of knowledge (epistemology) and meta-modeling knowledge before and after engaging in MBI. The qualitative data component of the research includes the observed written explanations and think-aloud protocol to characterize types of modeling practice that pre-service elementary teachers use to explain phenomena through the visual, written, and oral representations they create across five sets of iterative models. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. Partial funding is from the Robert Noyce Teacher Scholarship program. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
06/06/2024
|
06/06/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2430541
|
{'FirstName': 'Jaclyn', 'LastName': 'Murray', 'PI_MID_INIT': 'K', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jaclyn K Murray', 'EmailAddress': '[email protected]', 'NSF_ID': '000814085', 'StartDate': '06/06/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Mercer University', 'CityName': 'MACON', 'ZipCode': '312071515', 'PhoneNumber': '4783012700', 'StreetAddress': '1501 MERCER UNIVERSITY DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Georgia', 'StateCode': 'GA', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'GA02', 'ORG_UEI_NUM': 'FKLCLQFBA463', 'ORG_LGL_BUS_NAME': 'THE CORPORATION OF MERCER UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'The Corporation of Mercer University', 'CityName': 'MACON', 'StateCode': 'GA', 'ZipCode': '312071515', 'StreetAddress': '1501 MERCER UNIVERSITY DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Georgia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'GA02'}
|
[{'Code': '179500', 'Text': 'Robert Noyce Scholarship Pgm'}, {'Code': '199800', 'Text': 'IUSE'}]
|
2022~275625
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430541.xml'}
|
I-Corps: Translation potential of tethering above-ground storage tanks to prevent flood failures
|
NSF
|
06/15/2024
|
05/31/2025
| 50,000 | 50,000 |
{'Value': 'Standard Grant'}
|
{'Code': '15030000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'TI', 'LongName': 'Translational Impacts'}}
|
{'SignBlockName': 'Jaime A. Camelio', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922061'}
|
The broader impact of this I-Corps project is the development of a new methodology to prevent the failure of above ground oil storage tanks during floods. This solution is based on the development of a new methodology to tether new and existing above ground oil storage tanks to prevent failures during floods. Notably, out of approximately 5,000 tanks in the Houston Ship Channel, about a thousand tanks are located within the 100-year flood plain, making them vulnerable to storm surge-induced flood events. The failure of the tanks can lead to catastrophic oil spills. The proximity of the tanks to rivers and oceans increases the spill-induced environmental risks and chances of wildlife habitat damage in the surrounding areas. Furthermore, in many areas, such as the Houston Ship Channel and in Louisiana, tanks are located very close to residential communities. Potential spills caused by the failure of the tanks would expose these communities to hazardous substances. The improved flood safety tanks afforded by this tethering system will help improve the well-being of the surrounding communities and the environment. Furthermore, several regional economies, such as in Louisiana and Houston, TX, depend on industries that use these tanks extensively. The improved safety of tanks can make economies and communities that are dependent on these industries more resilient to floods.<br/><br/>This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. The solution uses anchor chairs, steel cables, and screw/helical piles to tether new and existing above ground oil storage tanks to prevent failures during floods. The steel cables will connect the anchor char that will be welded to the tank with the helical pile which will be embedded into the ground. The solution will allow controlled flotation of the tank during floods to avoid failure of the bottom plate, located on the underside of the tank. The existing anchor chair designs only consider vertical forces, so controlled floatation of the tanks also requires anchor chairs to sustain horizontal forces. The new design for anchor chairs can sustain a horizontal force of up to 36% of the vertical force. Computer simulations were used to develop the design for the new anchor chair. Industry feedback will be used to further develop this solution and the anchor chair design.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
06/11/2024
|
06/11/2024
|
None
|
Grant
|
47.084
|
1
|
4900
|
4900
|
2430546
|
[{'FirstName': 'Sabarethinam', 'LastName': 'Kameshwar', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Sabarethinam Kameshwar', 'EmailAddress': '[email protected]', 'NSF_ID': '000812667', 'StartDate': '06/11/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Santosh', 'LastName': 'Ghimire', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Santosh Ghimire', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A05PF', 'StartDate': '06/11/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Louisiana State University', 'CityName': 'BATON ROUGE', 'ZipCode': '708030001', 'PhoneNumber': '2255782760', 'StreetAddress': '202 HIMES HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Louisiana', 'StateCode': 'LA', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_ORG': 'LA06', 'ORG_UEI_NUM': 'ECQEYCHRNKJ4', 'ORG_LGL_BUS_NAME': 'LOUISIANA STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Louisiana State University', 'CityName': 'BATON ROUGE', 'StateCode': 'LA', 'ZipCode': '708030001', 'StreetAddress': '202 HIMES HALL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Louisiana', 'CountryFlag': '1', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_PERF': 'LA06'}
|
{'Code': '802300', 'Text': 'I-Corps'}
|
2024~50000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430546.xml'}
|
NLI: Research: A Collaborative Approach to Curricular Transformation: Leveraging Institutional Experience to Advance Sustainable Engineering Education
|
NSF
|
09/01/2024
|
08/31/2026
| 866,879 | 866,879 |
{'Value': 'Standard Grant'}
|
{'Code': '07050000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'EEC', 'LongName': 'Div Of Engineering Education and Centers'}}
|
{'SignBlockName': 'Matthew A. Verleger', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922961'}
|
Our world is at a critical juncture facing environmental and societal challenges that demand innovative solutions from the engineering sector. This project seeks to transform engineering education by deeply integrating sustainability concepts into the curricula across three diverse universities: Arizona State University, Kennesaw State University, and Villanova University. This transformative initiative aims to fundamentally reshape how future engineers are trained, emphasizing the crucial role of sustainability in engineering practices. This project aligns with the goals of the National Science Foundation and The Lemelson Foundation who both strive to advance science and engineering education, addressing environmental and social sustainability, thereby enhancing the capability of the next generation of engineers to drive sustainable development. In this project, we will pioneer a network that promotes systematic improvements in engineering educational practices to prepare students to be systems thinkers and sustainable in their approaches. Simultaneously, this network will offer faculty a community that they can rely on in their continuous practice of learning, analyzing, and integrating evolving sustainability concepts into their courses. This initiative serves as a public testament to the value of investing in educational transformations that prepare engineers to tackle environmental and social challenges. <br/><br/>The project will be executed in three phases over a period of two years, employing a dual-layered approach to engage both faculty and students in the transformative educational process. The initial phase involves establishing a network and developing collaborative action research projects, which enable faculty members from three institutes to explore and refine how sustainability concepts are implemented in their classrooms. The subsequent phase focuses on the continuous refinement of these practices in a collaborative community of practice through iterative action research cycles—planning, acting, observing, and reflecting. This approach not only aims to improve engineering teaching methods but also to deepen our understanding of the dynamics influencing faculty motivations and challenges in integrating sustainability into engineering education. The final phase focuses on dissemination, aiming to scale successful practices and foster a broader adoption of sustainability-focused education in engineering. Research questions will uncover the curricular and instructional changes that promote student learning of sustainability and the factors affecting faculty efforts of sustainability integration across diverse institutional contexts. Anticipated outcomes include the documentation of effective instructional strategies that enhance student understanding of sustainability in engineering problems, the advancement of faculty teaching methods, and better understanding of the processes that aid engineering faculty in integrating sustainability into their teaching. Ultimately, this project seeks to foster a cultural shift towards sustainability in engineering education, thereby equipping future engineers with the knowledge and skills necessary to lead societal progress towards a more sustainable and equitable world.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/02/2024
|
08/02/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2430560
|
[{'FirstName': 'Nadia', 'LastName': 'Kellam', 'PI_MID_INIT': 'N', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Nadia N Kellam', 'EmailAddress': '[email protected]', 'NSF_ID': '000255687', 'StartDate': '08/02/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Bridget', 'LastName': 'Wadzuk', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Bridget M Wadzuk', 'EmailAddress': '[email protected]', 'NSF_ID': '000154566', 'StartDate': '08/02/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Roneisha', 'LastName': 'Worthy', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Roneisha Worthy', 'EmailAddress': '[email protected]', 'NSF_ID': '000745311', 'StartDate': '08/02/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Deeksha', 'LastName': 'Seth', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Deeksha Seth', 'EmailAddress': '[email protected]', 'NSF_ID': '000818268', 'StartDate': '08/02/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Medha', 'LastName': 'Dalal', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Medha Dalal', 'EmailAddress': '[email protected]', 'NSF_ID': '000844324', 'StartDate': '08/02/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'Arizona State University', 'CityName': 'TEMPE', 'ZipCode': '852813670', 'PhoneNumber': '4809655479', 'StreetAddress': '660 S MILL AVENUE STE 204', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Arizona', 'StateCode': 'AZ', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'AZ04', 'ORG_UEI_NUM': 'NTLHJXM55KZ6', 'ORG_LGL_BUS_NAME': 'ARIZONA STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Arizona State University', 'CityName': 'TEMPE', 'StateCode': 'AZ', 'ZipCode': '852813670', 'StreetAddress': '660 S MILL AVENUE STE 204', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Arizona', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'AZ04'}
|
{'Code': '134000', 'Text': 'EngEd-Engineering Education'}
|
2024~866879
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430560.xml'}
|
EAGER: Empowering African American STEM Talent: Enhancing Semiconductor and Microelectronics Expertise Through Targeted Research and Mentorship at an HBCU
|
NSF
|
08/01/2024
|
07/31/2026
| 299,924 | 299,924 |
{'Value': 'Standard Grant'}
|
{'Code': '11060000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'EES', 'LongName': 'Div. of Equity for Excellence in STEM'}}
|
{'SignBlockName': 'Tori Rhoulac Smith', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922315'}
|
In a collaboration between the NSF Eddie Bernice Johnson INCLUDES Initiative and the NSF Research Experience and Mentoring (REM) programs, EArly-concept Grants for Exploratory Research (EAGERs) were considered under NSF Dear Colleague Letter 24-062 to broaden participation and develop the workforce in microelectronics through research experiences and structured mentoring. This project is establishing an academic training model that combines practical, hands-on research experiences and structured mentoring to deepen student engagement with cutting-edge technologies and methodologies in microelectronics fields. Junior level, undergraduate students majoring in electrical engineering or electrical engineering technology engage in research focused on generative artificial intelligence (AI) in semiconductor manufacturing to automate chip design, optimize production, and advance chip performance and energy efficiency. Faculty mentors guide students in research aligned with current industry challenges and use a conceptual framework, guided by the Anti-Deficit Achievement Framework, Social Cognitive Career Theory, and Prosocial Motivation, to enhance students’ educational experiences.<br/><br/>Section 10318 of the CHIPS and Science Act of 2022 promotes research and “innovative approaches to developing, improving, and expanding evidence-based education and workforce development activities and learning experiences at all levels of education in fields and disciplines related to microelectronics,” including partnerships that broaden participation in microelectronics education. Funds for this project were provided, in part, by the CHIPS and Science Act of 2022. This project is also funded by the Louis Stokes Alliances for Minority Participation (LSAMP), which aims to increase STEM degrees to underrepresented populations and supporting research on STEM participation and assessment of LSAMP program impacts.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/29/2024
|
07/29/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2430566
|
[{'FirstName': 'Chao', 'LastName': 'Li', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Chao Li', 'EmailAddress': '[email protected]', 'NSF_ID': '000082208', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Shonda', 'LastName': 'Bernadin', 'PI_MID_INIT': 'L', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Shonda L Bernadin', 'EmailAddress': '[email protected]', 'NSF_ID': '000652599', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Simon', 'LastName': 'Foo', 'PI_MID_INIT': 'Y', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Simon Y Foo', 'EmailAddress': '[email protected]', 'NSF_ID': '000987853', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Tejal', 'LastName': 'Mulay', 'PI_MID_INIT': 'P', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Tejal P Mulay', 'EmailAddress': '[email protected]', 'NSF_ID': '000854407', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'Florida Agricultural and Mechanical University', 'CityName': 'TALLAHASSEE', 'ZipCode': '323070001', 'PhoneNumber': '8505993531', 'StreetAddress': '1700 LEE HALL DR #201', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Florida', 'StateCode': 'FL', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'FL02', 'ORG_UEI_NUM': 'W8LKB16HV1K5', 'ORG_LGL_BUS_NAME': 'FLORIDA A & M UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'W8LKB16HV1K5'}
|
{'Name': 'Florida Agricultural and Mechanical University', 'CityName': 'TALLAHASSEE', 'StateCode': 'FL', 'ZipCode': '323070001', 'StreetAddress': '1700 LEE HALL DR #201', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Florida', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'FL02'}
|
[{'Code': '032Y00', 'Text': 'Eddie Bernice Johnson INCLUDES'}, {'Code': '913300', 'Text': 'Alliances-Minority Participat.'}]
|
2024~299924
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430566.xml'}
|
C2H2 EAGER: Soil and Toxicological Assays to Quantify and Mitigate Climate Change Effects on Human Exposure to Nanophase Aluminosilicate Minerals in Volcanic Soils
|
NSF
|
06/01/2024
|
05/31/2025
| 176,857 | 176,857 |
{'Value': 'Standard Grant'}
|
{'Code': '06010000', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'RISE', 'LongName': 'Div of Res, Innovation, Synergies, & Edu'}}
|
{'SignBlockName': 'Barbara Ransom', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927792'}
|
This research determines the nature, toxicity, and mobility of nanoscale mineral particles that form naturally in volcanic/volcanic, ash-rich soils. It examines whether mineralogical weathering products that develop from volcanic rock are the cause of podoconiosis, a skin disease that manifests like elephantitus, and is found in agricultural workers who labor barefoot in volcanic soils without adequate clothing and footwear. Human exposure to these mineral particles is limited by organic carbon in soil, which binds the particles into aggregates, as opposed to being free particles. Climate change and drought reduce the amount of organic carbon in soil, hence increases human exposure to the podoconiosis which is a debilitating condition. This project focuses on rural, subsistance, farm workers in Rwanda where podoconiosis is a common ailment. In addition to the mineralogical and toxicological work, the project includes assessment of agricultural practices that can prevent organic carbon loss as the climate changes. It also involves mineralogical sampling and high-resolution analysis to determine whether a specific mineral species, such as imogolite - a fiberous mineral with the same size and shape as asbestos can puncture and invade skin tissue, is responsible for the condition. Broader impacts of the work include reduction of a serious and debilitating health condition that has serious economic impacts for rural families in developing countries. In addition, by examinimg the crystaline structure and dimensions of volcanic soil minerals and by studying how organic matter stabilizes mineral particles in soils, this project will contribute to understanding soil properties not only in Africa and Rwanda, but across all nations as the climate changes. The project establishes a new international partnership between soil scientists and toxicologists in the US, Europe and Africa Rift countries. It will support a female graduate student and educate undergraduate graduate scholars in Africa and the US that come from populations underrepresented in Earth science. <br/><br/>This project will collect and study soils from agricultural regions of Rwanda where there is significant podoconiosis prevalence. Nanoscale minerals in soils will be extracted using chemical and mechanical methods. They will be characterized using X-ray diffraction, electron microscopy, and other high-resolution imaging and analytical methods. The toxicity of the extracted minerals will be quantified using toxicological and gene expression methods by collaborators in the UK and France. Our collaborators, one of which is from the Unviersity of Swansea Faculty of Medicine and who has a history of podoconoisis work and is funded under other auspices, will use mammalian immune cells that will be exposed to particles extracted from volcanic soils to assess effects on cell viability and non-lethal signatures of immune response. Next-generation DNA sequencing will identify up- or down-regulation of inflammatory pathways. The strength of the binding of mineral particles to soil, which will be done in the US part of the study, will be quantified using a torsional rheometry method. This shears soil samples and quantifies particles transferred to a surrogate of human skin. The US part of the study will develop methods to mitigate anticipated climate change effects on particle exposure by exploring and manipulating organic carbon and its type and quantity in soils to enhance soil particle aggregation which can mitigate the occurrence of podoconiosis.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
05/01/2024
|
05/01/2024
|
None
|
Grant
|
47.050
|
1
|
4900
|
4900
|
2430594
|
{'FirstName': 'Benjamin', 'LastName': 'Gilbert', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Benjamin Gilbert', 'EmailAddress': '[email protected]', 'NSF_ID': '000842884', 'StartDate': '05/01/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of California-Berkeley', 'CityName': 'BERKELEY', 'ZipCode': '947101749', 'PhoneNumber': '5106433891', 'StreetAddress': '1608 4TH ST STE 201', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'CA12', 'ORG_UEI_NUM': 'GS3YEVSS12N6', 'ORG_LGL_BUS_NAME': 'REGENTS OF THE UNIVERSITY OF CALIFORNIA, THE', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of California, Berkeley', 'CityName': 'berkeley', 'StateCode': 'CA', 'ZipCode': '947101749', 'StreetAddress': '1608 4th St, Suite 201', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'CA12'}
|
{'Code': '300Y00', 'Text': 'Climate Impact on Human Health'}
|
2024~176857
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430594.xml'}
|
Conference: Santa Cruz Developmental Biology Meeting 2024
|
NSF
|
07/01/2024
|
06/30/2025
| 15,000 | 15,000 |
{'Value': 'Standard Grant'}
|
{'Code': '08090000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'IOS', 'LongName': 'Division Of Integrative Organismal Systems'}}
|
{'SignBlockName': 'Anna Allen', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928011'}
|
The Santa Cruz Developmental Biology Conference 2024 (SCDB) brings together scientists, researchers, educators, and students to explore unifying principles of development and homeostasis in a broad diversity of animal and plant species. The conference fosters interdisciplinary collaborations that will lead to innovative solutions for accelerating scientific breakthroughs with immediate implications for reproductive and regenerative medicine. The SCDB meeting plays an important role in training the next generation of developmental biologists, by providing a platform for trainees to present their research. These opportunities inspire and equip students with a set of skills to pursue diverse careers in life sciences. Additionally, the conference aims to help equip the next generation of developmental biologists to serve as professional stewards for our society and planet through one of its broader impact activities- the organization of a workshop focused on communicating science and building sustainability into research labs. Enhanced communication to the lay-public and awareness of the environmental impact of scientific research will motivate researchers to incorporate sustainably-minded practices into their work culture. Additional broader impact activities include travel support for 30 participants from historically excluded groups and early career stages. SCDB serves as a catalyst for scientific innovation, education, and societal benefit. Its impact extends beyond the scientific community, contributing to public health and education by fostering a more knowledgeable and scientifically engaged society.<br/><br/>Fundamental research in developmental biology has transformed our understanding of congenital diseases, stem cell biology, oncology, and regenerative medicine. Ongoing work at the cutting edge of this field promises to provide novel insights in the years to come, with important implications for our understanding of genetic, molecular and cellular processes of multicellular life, and with important implications for understanding how interacting developmental processes give rise to emergent properties that result in the development of complex phenotypes and structures. The 2024 meeting is focused on unifying principles of organismal development and a group of leading scientists have been invited to discuss diverse experimental and theoretical developmental models across diverse organisms. To address fundamental challenges of development of multicellular life, the 2024 meeting is organized around the following integral topics: Cell-Cell Communication, Theory and Modeling in Development, Active Matter and Mechanics, Convergent and Divergent Morphogenesis, Cellular Transitions and Plasticity, Information Processing and Gene Regulatory Networks and New Technologies and Synthetic Approaches. Broader impact activities include workshops on both scientific communication and designing environmental sustainability into research labs to prepare the next generation of developmental biologists to serve as stewards for society and our planet. This proposal will financially support members of historically excluded groups to be able to attend the meeting. In sum, the 2024 meeting will build on past successes while incorporating best practices for inclusive conferences, highlighting recent breakthroughs, and serving as a catalyst for new approaches and ideas in this rapidly evolving field.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
06/07/2024
|
06/07/2024
|
None
|
Grant
|
47.074
|
1
|
4900
|
4900
|
2430601
|
{'FirstName': 'Ali', 'LastName': 'Shariati', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ali Shariati', 'EmailAddress': '[email protected]', 'NSF_ID': '000850715', 'StartDate': '06/07/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of California-Santa Cruz', 'CityName': 'SANTA CRUZ', 'ZipCode': '950641077', 'PhoneNumber': '8314595278', 'StreetAddress': '1156 HIGH ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '19', 'CONGRESS_DISTRICT_ORG': 'CA19', 'ORG_UEI_NUM': 'VXUFPE4MCZH5', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CALIFORNIA SANTA CRUZ', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of California-Santa Cruz', 'CityName': 'SANTA CRUZ', 'StateCode': 'CA', 'ZipCode': '950641077', 'StreetAddress': '1156 HIGH ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '19', 'CONGRESS_DISTRICT_PERF': 'CA19'}
|
{'Code': '111900', 'Text': 'Animal Developmental Mechanism'}
|
2024~15000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430601.xml'}
|
Advanced Inverse Design of Planar Microwave and Millimeter Wave Devices
|
NSF
|
01/01/2025
|
12/31/2027
| 545,961 | 545,961 |
{'Value': 'Standard Grant'}
|
{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}
|
{'SignBlockName': 'Jenshan Lin', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927360'}
|
This project aims to revolutionize the field of microwave circuit design by developing an advanced inverse design (InvDes) framework. Microwave circuits are essential in communication and sensing systems critical for consumer electronics, healthcare, and defense, and their design significantly impacts the overall performance, cost, and efficiency of these systems. Current design methods primarily rely on human engineers leveraging their training and experience to craft circuit layouts. In contrast, InvDes lets a computer algorithm find designs that maximize desired performance within specific constraints, discovering new topologies and shapes beyond human intuition. This project will create a systematic framework for the InvDes of planar microwave devices -- filters, splitters, baluns, antennas, and more -- meeting complex performance requirements and shape/size or fabrication constraints demanded by diverse application. The project will support the education of the nation's next generation of electronic engineers, preparing them to excel in the era of advanced computing by involving them in cutting-edge research and developing new curriculum modules. The designs generated by the proposed approach will be fabricated and validated alongside industry partners, solving outstanding challenges in microwave engineering and immediately benefitting a wide array of applications from autonomous vehicle radars to next-generation wireless communication.<br/><br/>This project seeks to create a unified framework for the inverse design (InvDes) of planar microwave and millimeter wave devices, moving beyond conventional circuit design techniques to explore a substantially broader design space. Realizing this goal requires parameterization techniques that give the algorithm maximal freedom to design devices of any necessary topology and shape, powerful optimizers pioneered for use in machine learning tasks, and highly efficient simulators such as GPU-accelerated finite difference methods and versatile finite element and boundary element solvers. For the first time, multilayer devices will be fully machine designed, with both metal layers and via placement controlled by the algorithm, enabling InvDes of the full range of modern microwave components. To address the non-convexity of the design landscape, which generally demands many trials with random initial conditions to find high-performing devices, our initializations will be pre-optimized by first minimizing a convex dual problem with relaxed physics. The designs generated by this algorithm will be fabricated using both macroscopic printed circuit board (PCB) and nanoscale complementary metal-oxide semiconductor (CMOS) technology. Experimental verification of device performance will utilize broadband network analyzers, as well as microwave impedance microscopy which permits mapping of the local electric field distribution in operando with exquisite spatial resolution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/12/2024
|
08/12/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2430603
|
[{'FirstName': 'Eric', 'LastName': 'Ma', 'PI_MID_INIT': 'Y', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Eric Y Ma', 'EmailAddress': '[email protected]', 'NSF_ID': '000918321', 'StartDate': '08/12/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Jun-Chau', 'LastName': 'Chien', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jun-Chau Chien', 'EmailAddress': '[email protected]', 'NSF_ID': '000921699', 'StartDate': '08/12/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'University of California-Berkeley', 'CityName': 'BERKELEY', 'ZipCode': '947101749', 'PhoneNumber': '5106433891', 'StreetAddress': '1608 4TH ST STE 201', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'CA12', 'ORG_UEI_NUM': 'GS3YEVSS12N6', 'ORG_LGL_BUS_NAME': 'REGENTS OF THE UNIVERSITY OF CALIFORNIA, THE', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of California-Berkeley', 'CityName': 'BERKELEY', 'StateCode': 'CA', 'ZipCode': '947101749', 'StreetAddress': '1608 4TH ST STE 201', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'CA12'}
|
{'Code': '756400', 'Text': 'CCSS-Comms Circuits & Sens Sys'}
|
2024~545961
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430603.xml'}
|
Building capacity, community, and knowledge for International Network-to-Network Research Collaboration
|
NSF
|
09/01/2024
|
08/31/2027
| 933,987 | 933,987 |
{'Value': 'Standard Grant'}
|
{'Code': '01090000', 'Directorate': {'Abbreviation': 'O/D', 'LongName': 'Office Of The Director'}, 'Division': {'Abbreviation': 'OISE', 'LongName': 'Office Of Internatl Science &Engineering'}}
|
{'SignBlockName': 'Allen Pope', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928030'}
|
International network-to-network collaboration can enable scientific researchers across the world to collectively identify gaps in knowledge and areas for future research, further advancing the frontiers of science while training the next generation of U.S. researchers. Building such international collaborations is a complex process that requires coordination and communication to support data sharing, training, knowledge transfer, and relationship building. The Toolbox Dialogue Initiative Center (TDIC), based at Michigan State University, will support awardees the Accelerating Research Through International Network-to-Network Collaboration (AccelNet) researcher community by building collaborative capacity within AccelNet projects, facilitating a community of practice across cohorts, and expanding research on international network-to-network collaboration. <br/><br/>TDIC will support AccelNet awardees by providing newly funded networks of networks with coordinated activities utilizing team science facilitation methods and peer-to-peer interactions aimed at enhancing their collaborative efforts. The main activities of this project are: 1) annual, in-person meetings for members of awarded projects and professional development workshops for AccelNet early career researchers, 2) dialogue-based Toolbox workshops for the 2024, 2025 and 2026 AccelNet cohorts, 3) virtual interactive webinars and workshops, and 4) research on success conditions for large-scale international collaboration as reflected in AccelNet projects. Each new cohort will participate in team-focused Toolbox workshops designed to enhance communication and build team cohesion. Annual in-person meetings and virtual interactive sessions will support the continued growth of a community of practice centered on knowledge exchange to advance international network-to-network collaboration for scientific advancement and social learning across the cohorts. Continued study of the funded projects will expand the body of knowledge regarding success conditions for sustaining international networked collaborations. Drawing on previous work with multiple NSF programs, TDIC will develop new resources in this project that support the goals of the AccelNet program and contribute more broadly to team science training and facilitation.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/08/2024
|
08/08/2024
|
None
|
Grant
|
47.079
|
1
|
4900
|
4900
|
2430616
|
[{'FirstName': 'Michael', 'LastName': "O'Rourke", 'PI_MID_INIT': 'R', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': "Michael R O'Rourke", 'EmailAddress': '[email protected]', 'NSF_ID': '000408598', 'StartDate': '08/08/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Marisa', 'LastName': 'Rinkus', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Marisa A Rinkus', 'EmailAddress': '[email protected]', 'NSF_ID': '000572180', 'StartDate': '08/08/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'Michigan State University', 'CityName': 'EAST LANSING', 'ZipCode': '488242600', 'PhoneNumber': '5173555040', 'StreetAddress': '426 AUDITORIUM RD RM 2', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Michigan', 'StateCode': 'MI', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MI07', 'ORG_UEI_NUM': 'R28EKN92ZTZ9', 'ORG_LGL_BUS_NAME': 'MICHIGAN STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'VJKZC4D1JN36'}
|
{'Name': 'Michigan State University', 'CityName': 'EAST LANSING', 'StateCode': 'MI', 'ZipCode': '488242600', 'StreetAddress': '426 AUDITORIUM RD RM 2', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Michigan', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MI07'}
|
{'Code': '069Y00', 'Text': 'AccelNet - Accelerating Resear'}
|
2024~933987
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430616.xml'}
|
LTREB Renewal: Using forecasting and long-term experiments to understand ecological dynamics under novel conditions
|
NSF
|
12/01/2024
|
11/30/2029
| 643,550 | 515,244 |
{'Value': 'Continuing Grant'}
|
{'Code': '08010000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'DEB', 'LongName': 'Division Of Environmental Biology'}}
|
{'SignBlockName': 'Betsy Von Holle', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924974'}
|
Ecosystems and the services they provide are changing. This makes predictions for how systems will change crucial for decision making by land managers and policy makers. However, current capabilities for making ecological forecasts are limited. Making forecasts requires understanding how ecosystems will respond to changing conditions. Because ecosystems are governed by complex interactions among species and their environment, our knowledge from the past may provide limited information about the future as conditions change. Thus, it is critical to develop and assess our ability to make forecasts when novel conditions occur. For over 40 years, the Portal Project has been collecting data on mammals and plants as part of a long-term experiment in southeastern Arizona. Continuing data collection at this site provides a unique opportunity to (1) assess how the occurrence of novel conditions impact the ability to forecast the population sizes of mammals and (2) determine the best methods to forecast changes in ecological systems. This project will support the growing field of ecological forecasting by providing a high-quality, openly available data source for other researchers. The research team will also produce online educational materials to support classes to teach the next generation of ecological forecasters.<br/><br/>This research project will use the unique strengths of the Portal Project to improve ecological forecasting under novel conditions. Comparing the performance of forecasting approaches under novel conditions requires long-term data and novel environments. Over the past two decades, the environment at the Portal Project has become warmer and drier. This creates novel environmental conditions for species. Additionally, experiments at the site create novel combinations of species. Ongoing data collection will be used to assess: (1) if models with more ecological complexity perform better, (2) if data from experiments can improve forecasts, and (3) if forecasting models can handle rapid environmental changes. This research will use an automated forecasting system that serves as a model for ecological forecasting. The project requires ongoing data collection to test forecasts and to provide information on ecological changes as species and the environment change.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/24/2024
|
07/24/2024
|
None
|
Grant
|
47.074
|
1
|
4900
|
4900
|
2430620
|
[{'FirstName': 'Morgan', 'LastName': 'Ernest', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Morgan Ernest', 'EmailAddress': '[email protected]', 'NSF_ID': '000240686', 'StartDate': '07/24/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Ethan', 'LastName': 'White', 'PI_MID_INIT': 'P', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ethan P White', 'EmailAddress': '[email protected]', 'NSF_ID': '000246060', 'StartDate': '07/24/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'University of Florida', 'CityName': 'GAINESVILLE', 'ZipCode': '326111941', 'PhoneNumber': '3523923516', 'StreetAddress': '1523 UNION RD RM 207', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Florida', 'StateCode': 'FL', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'FL03', 'ORG_UEI_NUM': 'NNFQH1JAPEP3', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF FLORIDA', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Florida', 'CityName': 'GAINESVILLE', 'StateCode': 'FL', 'ZipCode': '326111941', 'StreetAddress': '1523 UNION RD RM 207', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Florida', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'FL03'}
|
{'Code': '112800', 'Text': 'Population & Community Ecology'}
|
2024~515244
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430620.xml'}
|
CIVIC-PG Track A: BUILT2AFFORD - Big Data Enabled Energy-Efficiency and Health Assessments to Provide Affordable Housing
|
NSF
|
10/01/2024
|
03/31/2025
| 74,211 | 74,211 |
{'Value': 'Standard Grant'}
|
{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}
|
{'SignBlockName': 'David Corman', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928754'}
|
The United States faces a severe shortage of affordable housing, particularly for communities with extremely low incomes. This crisis is compounded by the outdated infrastructure of existing housing, which results in high energy costs and inadequate living conditions. This project, BUILT2AFFORD, aims to address this dual challenge by leveraging advanced technology and strong community partnerships to enhance the energy efficiency of affordable housing. By focusing on low-cost passive design strategies, such as improved ventilation and shading, this project seeks to reduce the energy burden on low-income households and improve their living conditions. This project is significant because it tackles the pressing need for affordable, energy-efficient housing in the Midwest, particularly in South Bend, Indiana. By developing a framework to pre-identify housing units suitable for retrofits, our research will enable more targeted and effective interventions. The broader impact of this work includes reducing energy costs for low-income families, mitigating heat-related health risks, and contributing to the sustainability goals of local communities. The successful implementation of this project could serve as a model for other regions, demonstrating how affordable housing can be preserved and improved through innovative, data-driven approaches.<br/><br/>The BUILT2AFFORD project aims to enhance the energy efficiency of affordable housing by developing, testing, and validating a tool that uses machine learning algorithms and Google Street View images. This tool will automate the identification of housing units suitable for low-cost passive retrofits. In Stage 1, we will collaborate with the City of South Bend and Near Northwest Neighborhood to conduct audits of 10-20 houses to create archetype layouts for thermal comfort simulations. We will develop computer vision algorithms to extract passive design indicators from Street View images, combining this with property data to build the BUILT2AFFORD model. In Stage 2, the model will be validated by retrofitting two testbed buildings with passive design strategies. Sensors will monitor energy usage and indoor environmental conditions over eight months. The data will refine and calibrate the model for accuracy and reliability. The project will produce the BUILT2AFFORD tool, a dashboard pre-identifying affordable housing units for retrofits. It will visualize data on design indicators, energy efficiency, and health risks, aiding homeowners, policymakers, and public health officials. This project supports energy efficiency, improved home comfort, and equitable health outcomes, contributing to broader climate resilience efforts.<br/><br/>This project is in response to the Civic Innovation Challenge program’s Track A. Climate and Environmental Instability - Building Resilient Communities through Co-Design, Adaption, and Mitigation and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/13/2024
|
08/13/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2430623
|
[{'FirstName': 'Chaoli', 'LastName': 'Wang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Chaoli Wang', 'EmailAddress': '[email protected]', 'NSF_ID': '000510655', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Ming', 'LastName': 'Hu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ming Hu', 'EmailAddress': '[email protected]', 'NSF_ID': '000730479', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Matthew', 'LastName': 'Sisk', 'PI_MID_INIT': 'L', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Matthew L Sisk', 'EmailAddress': '[email protected]', 'NSF_ID': '000841930', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'University of Notre Dame', 'CityName': 'NOTRE DAME', 'ZipCode': '465565708', 'PhoneNumber': '5746317432', 'StreetAddress': '940 GRACE HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Indiana', 'StateCode': 'IN', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'IN02', 'ORG_UEI_NUM': 'FPU6XGFXMBE9', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF NOTRE DAME DU LAC', 'ORG_PRNT_UEI_NUM': 'FPU6XGFXMBE9'}
|
{'Name': 'University of Notre Dame', 'CityName': 'NOTRE DAME', 'StateCode': 'IN', 'ZipCode': '465566031', 'StreetAddress': '940 GRACE HALL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Indiana', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'IN02'}
|
{'Code': '033Y00', 'Text': 'S&CC: Smart & Connected Commun'}
|
2024~74211
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430623.xml'}
|
OP: Enhancing detectivity of avalanche photodiodes by engineering correlated noise
|
NSF
|
09/01/2024
|
08/31/2027
| 479,925 | 479,925 |
{'Value': 'Standard Grant'}
|
{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}
|
{'SignBlockName': 'Margaret Kim', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922967'}
|
A nontechnical description of the project:<br/><br/>Avalanche Photodiodes (APDs) are widely used for optical communications, environmental monitoring, imaging, and night vision. They operate by employing a large electric field to crash photogenerated carriers into each other, causing an avalanche of free carriers by impact ionization, leading to a large gain in photocurrent that can increase the sensitivity of optical receivers to the extreme of single photon detection. However, since these impact ionization events are random, they also amplify shot noise arising from the granularity of charges. A key goal in APD research is to lower the noise arising from this gain mechanism to near-silicon values, albeit at small material bandgaps sensitive to longer infrared wavelengths. The goal of this proposal is to examine if the random noise can be reduced deterministically by correlating the charges. Recent experiments in mercury and antimony-containing APDs show dramatic noise reduction. This proposal will explore a possible origin due to ‘dead spaces’, over which the mobile charges build up adequate energy and momentum to tear away other bound charges from their parent atoms. In heavy element-based materials with relativistic spin-charge interactions and well-separated bands, the high internal fields can localize the charges to the start of these dead spaces, which will periodically correlate the charges and reduce the noise. A thorough understanding of the impact of correlated noise – both theoretically with high-power computational models as well as experimentally with material growth, fabrication, and characterization, will provide insight into fundamental device physics and enable design of ultralow noise APDs. The result will be a significant breakthrough in optical receiver sensitivity across a broad range of commercial, military, and research applications, including imaging arrays, optical communications, chemical and biological sensing, astronomical observations, and quantum optics. Educational tools, training videos, and outreach measures will bring the research and the underlying science to the mainstream scientific community and the next generation of student practitioners in this area. <br/><br/> A technical description of the project:<br/>Avalanche Photodiodes (APDs) use impact ionization under high-bias fields to amplify the current from a few photogenerated carriers. However, the stochastic nature of the underlying gain mechanism inevitably amplifies shot noise owing to the granularity of charges. McIntyre’s local field model has been used successfully for 60+ years to characterize this noise in APDs, using the excess-noise-factor figure of merit. The excess noise is primarily controlled by the average gain and the ratio of the minority to majority carrier ionization rates (i.e., how bipolar the chain reactions are). The aim of this proposal is to explore, explain and exploit a series of persistent observations in homojunction APDs containing antimony and mercury, and impact ionization engineered (I2E) heterojunctions with negative band-offsets, where the measured excess noise consistently lies below the fundamental noise limit predicted by McIntyre’s model, especially for lower gain values. In particular, the homojunction APDs exhibit this sub-McIntyre noise characteristic up to high gains. Viewed through the conventional lens of uncorrelated noise, this observation suggests that one of the two ionization rates is unphysically negative. In the proposed program, we will combine state-of-the-art material and transport modeling with digital and random quarternary and ternary alloy growth, APD fabrication, and characterization of current gain and excess noise, to demonstrate that a likely origin of sub-McIntyre noise is the spatial correlation between individual impact ionization events imposed by high field non-local effects (‘dead space’) in homojunction APDs, and the abrupt threshold reduction and charge heating in heterojunction I2E APDs. Educational tools, training videos and outreach measures will bring the research and the underlying science to the mainstream scientific community and next generation of student practitioners in this area.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/24/2024
|
07/24/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2430629
|
[{'FirstName': 'Avik', 'LastName': 'Ghosh', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Avik Ghosh', 'EmailAddress': '[email protected]', 'NSF_ID': '000284714', 'StartDate': '07/24/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Joe', 'LastName': 'Campbell', 'PI_MID_INIT': 'C', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Joe C Campbell', 'EmailAddress': '[email protected]', 'NSF_ID': '000366852', 'StartDate': '07/24/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'University of Virginia Main Campus', 'CityName': 'CHARLOTTESVILLE', 'ZipCode': '229034833', 'PhoneNumber': '4349244270', 'StreetAddress': '1001 EMMET ST N', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Virginia', 'StateCode': 'VA', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'VA05', 'ORG_UEI_NUM': 'JJG6HU8PA4S5', 'ORG_LGL_BUS_NAME': 'RECTOR & VISITORS OF THE UNIVERSITY OF VIRGINIA', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Virginia Main Campus', 'CityName': 'CHARLOTTESVILLE', 'StateCode': 'VA', 'ZipCode': '229034833', 'StreetAddress': '1001 EMMET ST N', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Virginia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'VA05'}
|
{'Code': '151700', 'Text': 'EPMD-ElectrnPhoton&MagnDevices'}
|
2024~479925
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430629.xml'}
|
Regulating Electrode-Electrolyte Interface via Patterned Solid Polymer Electrolytes for Solid-State Batteries
|
NSF
|
09/01/2024
|
08/31/2027
| 384,954 | 384,954 |
{'Value': 'Standard Grant'}
|
{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}
|
{'SignBlockName': 'Carole Read', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922418'}
|
Despite the significant efforts devoted to solid-state battery research and the impressive performance improvement accomplished during the past two decades, a fundamental understanding of metal nucleation, growth, and interaction with solid electrolytes remains elusive. This research aims to bridge this knowledge gap by establishing a new electrolyte system to systematically decouple complex factors such as local mechanical, chemical, and electrochemical effects on lithium and sodium electrodeposition. The novel patterned solid polymer electrolytes (pSPEs) are designed to have micro-size features that can be used to understand the battery charging and discharging processes. This class of unique pSPEs is anticipated to allow for a detailed mechanistic study of metal nucleation and growth at the electrode/electrolyte interface. Thus, the research addresses a grand challenge facing the energy research community, and if successful, will lead to a new type of solid-state battery. The educational component of the project includes (1) developing class modules that will be used in graduate courses, (2) mentoring graduate and undergraduate students, and (3) involving high school students and teachers in the project’s research activities. <br/><br/>This project aims to fabricate a series of spatially heterogeneous solid polymer electrolytes for solid-state batteries. The patterned solid polymer electrolytes (pSPEs), fabricated using soft lithography, will possess spatially controlled heterogeneity at the metal anode-electrolyte interface, which allows for systematically decoupling the convoluted local mechanical, chemical, and electrochemical effects on lithium (Li) and sodium (Na) electrodeposition in solid-state batteries. The specific aims are (1) fabricating pSPEs with controlled spatial heterogeneity in various properties using soft lithography; (2) understanding the nucleation mechanism of lithium and sodium metal at the electrode-pSPEs interface; (3) understanding the growth mechanism of lithium and sodium metal at the electrode-pSPEs interface. A library of pSPEs will be fabricated with controlled spatial heterogeneity varied from µm to >100 µm, selected based on the typical nucleation density of Li and Na. The pSPEs will serve as a new materials platform to investigate metal electrodeposition, and they will significantly improve fundamental understanding of the complex electrode/electrolyte interface in solid-state batteries. The knowledge gained from this project will benefit the next generation of battery design and pave the way for safer and more efficient energy storage solutions.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/01/2024
|
08/01/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2430632
|
{'FirstName': 'Christopher', 'LastName': 'Li', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Christopher Li', 'EmailAddress': '[email protected]', 'NSF_ID': '000275409', 'StartDate': '08/01/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Drexel University', 'CityName': 'PHILADELPHIA', 'ZipCode': '191042875', 'PhoneNumber': '2158956342', 'StreetAddress': '3141 CHESTNUT ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'StateCode': 'PA', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'PA03', 'ORG_UEI_NUM': 'XF3XM9642N96', 'ORG_LGL_BUS_NAME': 'DREXEL UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Drexel University', 'CityName': 'PHILADELPHIA', 'StateCode': 'PA', 'ZipCode': '191042875', 'StreetAddress': '3141 CHESTNUT ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'PA03'}
|
{'Code': '764400', 'Text': 'EchemS-Electrochemical Systems'}
|
2024~384954
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430632.xml'}
|
Conference: American Chemical Society Fall 2024 Graduate Student Symposium, Denver, CO, August 18-22
|
NSF
|
07/01/2024
|
12/31/2024
| 18,416 | 18,416 |
{'Value': 'Standard Grant'}
|
{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}
|
{'SignBlockName': 'Robert McCabe', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924826'}
|
The Graduate Student Symposium (GSS) is a day-long, student-organized event held during the Spring and Fall National Meetings of the American Chemical Society (ACS). This activity has been conducted since 2005 under the guidance of the Graduate Student Symposium Planning Committee of the American Chemical Society (ACS), typically with base funding from ACS supplemented by funding from other organizations. A team of students from the University of Buffalo has been selected as the Graduate Student Symposium Planning Committee (GSSPC) to organize this symposium at the ACS Fall 2024 National Meeting in Denver, Colorado. The GSSPC is responsible for all aspects of the symposium, including selecting a topic, inviting speakers, securing funds, and recruiting and mentoring the next GSSPC. The symposium's theme, "Breaking the Mold: Building Communication to Promote Green and Sustainable Practices," revolves around examining and discussing innovative approaches to implementing green and sustainable practices in both academia and industry. The primary objectives of the symposium are: (1) to raise awareness about the relevance and need for green chemistry in academic and industrial settings, (2) to establish a collaborative platform for the exchange of best practices among the attendees, and (3) to promote the notion that green and sustainable practices are achievable without compromising quality, cost, and efficiency. To maximize engagement and knowledge dissemination, the symposium will consist of two events: 1) Lectures by invited speakers (i.e., individuals from academia, scientists who work at government agencies, and active members working in industry), and 2) Green Connect: A networking event held to facilitate engagement among speakers, sponsors, and attendees. This gathering will create an environment conducive to forging meaningful connections that could transcend the symposium. Invited speakers have been thoughtfully chosen by the planning committee as distinguished lecturers to ensure a comprehensive and holistic perspective of the dynamic and evolving landscapes of green and sustainable chemistry.<br/><br/>The symposium aims to address the pressing need for environmental protection and sustainability by fostering essential dialogue between the attendees and representatives from academic institutions, industries, and non-profit organizations. Moreover, the symposium intends to promote equity and diversity, inclusivity, and accessibility in STEM. The selection of speakers reflects a deliberate effort to represent a diverse scientific and cultural community to provide attendees with role models whose experiences and challenges resonate with a diverse audience. Additionally, the GSSPC presents a valuable opportunity for the professional development of both the current and future Graduate Student Symposium Planning committees.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
06/12/2024
|
06/12/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2430639
|
{'FirstName': 'Luis', 'LastName': 'De Jesus Baez', 'PI_MID_INIT': 'R', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Luis R De Jesus Baez', 'EmailAddress': '[email protected]', 'NSF_ID': '000877925', 'StartDate': '06/12/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'SUNY at Buffalo', 'CityName': 'AMHERST', 'ZipCode': '142282577', 'PhoneNumber': '7166452634', 'StreetAddress': '520 LEE ENTRANCE STE 211', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '26', 'CONGRESS_DISTRICT_ORG': 'NY26', 'ORG_UEI_NUM': 'LMCJKRFW5R81', 'ORG_LGL_BUS_NAME': 'RESEARCH FOUNDATION FOR THE STATE UNIVERSITY OF NEW YORK, THE', 'ORG_PRNT_UEI_NUM': 'GMZUKXFDJMA9'}
|
{'Name': 'SUNY at Buffalo', 'CityName': 'Buffalo', 'StateCode': 'NY', 'ZipCode': '142604600', 'StreetAddress': '532 Natural Science Complex', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '26', 'CONGRESS_DISTRICT_PERF': 'NY26'}
|
{'Code': '140100', 'Text': 'Catalysis'}
|
2024~18416
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430639.xml'}
|
Participant Support for Titans of the Tiny Symposium; Evanston, Illinois; 12-13 July 2024
|
NSF
|
06/01/2024
|
11/30/2024
| 25,000 | 25,000 |
{'Value': 'Standard Grant'}
|
{'Code': '07030000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CMMI', 'LongName': 'Div Of Civil, Mechanical, & Manufact Inn'}}
|
{'SignBlockName': 'Khershed Cooper', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927017'}
|
This award provides participant support for younger and broader groups of researchers to attend the Titans of the Tiny Symposium at Northwestern University in Evanston, Illinois, 12-13 July 2024. The symposium focuses on research and development activities in nanoscience and nanotechnology in the last thirty years, as well as perspectives for the future. World renowned researchers present their research results on nanoscience and nanotechnology in oral sessions. The symposium impacts the materials science, chemistry, physics, biology, and engineering communities. Priority is given to participation by women and under-represented minorities, which promotes diverse participation at the symposium. This award benefits the nation through the education of a skilled science and engineering workforce, which is better prepared to provide transformative solutions to the challenges in their chosen fields. This symposium plays an important role in supporting and sustaining the field of nanoscience and nanotechnology, which has important applications in energy, medicine, microelectronics, and quantum technologies, which are National priorities.<br/><br/>This participant support is expected to benefit the students’ and young researchers’ professional, scientific, and technical development. Attendance at the symposium gives the students and young faculty a broader view of nanoscience and nanotechnology, its fundamentals, and specifically its impact in surface coordination chemistry, catalysis, photonics, theory and modeling, microscopy, particle synthesis and shape control, metal-organic framework and supramolecular chemistry, organic materials, life and bioscience, lithography, polymer synthesis, materials discovery, and manufacturing. At the symposium, concepts and challenges in nanoscience and engineering are identified and presented, and attendees chart new paths forward in the field and rally a new generation of researchers toward them. The symposium is attended by US and international researchers, which provides an opportunity for a variety of perspectives to be presented and discussed. The symposium is an opportunity for participants to showcase their scientific accomplishments and interact with peers and colleagues in academia, government laboratories and industry.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
05/31/2024
|
05/31/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2430644
|
{'FirstName': 'Chad', 'LastName': 'Mirkin', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Chad A Mirkin', 'EmailAddress': '[email protected]', 'NSF_ID': '000191212', 'StartDate': '05/31/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Northwestern University', 'CityName': 'EVANSTON', 'ZipCode': '602080001', 'PhoneNumber': '3125037955', 'StreetAddress': '633 CLARK ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Illinois', 'StateCode': 'IL', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_ORG': 'IL09', 'ORG_UEI_NUM': 'EXZVPWZBLUE8', 'ORG_LGL_BUS_NAME': 'NORTHWESTERN UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Northwestern University', 'CityName': 'EVANSTON', 'StateCode': 'IL', 'ZipCode': '602080001', 'StreetAddress': '633 CLARK ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Illinois', 'CountryFlag': '1', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_PERF': 'IL09'}
|
[{'Code': '088Y00', 'Text': 'AM-Advanced Manufacturing'}, {'Code': '768100', 'Text': 'ENG NNI Special Studies'}]
|
2024~25000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430644.xml'}
|
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