Her research focuses on energy-efficient machine learning systems for edge and cloud computing. She is leading the Efficient and Intelligent Computing (EIC) Lab at Rice, which is exploring algorithm-, architecture-, and circuit-level techniques to develop machine learning systems for resource-constrained platforms. Dr. Lin received a Ph.D. degree in electrical and computer engineering from the University of Illinois at Urbana-Champaign in 2017. She has been working on analog and mixed-signal circuits, error resiliency techniques, and VLSI circuits and architectures for machine learning systems on resource-constrained platforms.