Jason Lee

Jason Lee

Associate professor, Princeton University

Jason Lee is an associate professor in Electrical Engineering and Computer Science (secondary) at Princeton University. Prior to that, he was in the Data Science and Operations department at the University of Southern California and a postdoctoral researcher at UC Berkeley working with Michael I. Jordan. Jason received his PhD at Stanford University advised by Trevor Hastie and Jonathan Taylor. His research interests are in the theory of machine learning, optimization, and statistics. Lately, he has worked on the foundations of deep learning, representation learning, and reinforcement learning. He has received the Samsung AI Researcher of the Year Award, NSF Career Award, ONR Young Investigator Award in Mathematical Data Science, Sloan Research Fellowship, NeurIPS Best Student Paper Award and Finalist for the Best Paper Prize for Young Researchers in Continuous Optimization.

Program Visits

Special Year on Large Language Models and Transformers, Part 2 , Spring 2025, Visiting Scientist
Modern Paradigms in Generalization, Fall 2024, Visiting Scientist
Special Year on Large Language Models and Transformers, Part 1, Fall 2024, Visiting Scientist
Summer Cluster: Deep Learning Theory, Summer 2022, Visiting Scientist
Learning and Games, Spring 2022, Visiting Scientist
Theory of Reinforcement Learning, Fall 2020, Visiting Scientist
Foundations of Deep Learning, Summer 2019, Visiting Scientist
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program
Modern Paradigms in Generalization
visiting
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program
Special Year on Large Language Models and Transformers, Part 1
visiting
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Fields
Machine learning (theory), artificial intelligence, statistics