His research interests include machine learning, computational linguistics, and biomedical informatics. He graduated from the University of Texas at Austin in 2007 with a PhD thesis on machine learning methods for information extraction. Since then, a major focus of his research has been on exploiting large scale weakly structured collections of documents for natural language processing applications. More recently, in collaboration with a group of diabetes experts, he has been working on machine learning models for medical informatics tasks such as blood glucose level prediction and glycemic variability detection. His research has been funded by grants from the National Science Foundation and Ohio University.