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Jason Lee is an associate professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. Prior to his current position, he served as an associate professor at Princeton University and was a researcher at Google DeepMind. He received his PhD in Computational and Applied Mathematics from Stanford University, where he was advised by Trevor Hastie and Jonathan Taylor. Following his doctoral studies, Jason completed a postdoctoral fellowship at UC Berkeley under the guidance of Michael Jordan. His research interests encompass theoretical aspects of machine learning, optimization, and statistics. Recently, he has focused on foundational issues in deep learning, representation learning, and reinforcement learning. Throughout his career, he has received several prestigious awards, including the Samsung AI Researcher of the Year Award, the NSF Career Award, the ONR Young Investigator Award in Mathematical Data Science, the Sloan Research Fellowship, and was a finalist for the NeurIPS Student Paper Award. He teaches advanced topics related to learning and decision making.
The Mathematics Subject GRE is required for the Fall 2026 admissions cycle. General GRE is optional.