Jason Lee

Senior Scientist,

Princeton University

Jason Lee is an associate professor in EECS and Statistics at UC Berkeley and a senior scientist at the Simons Institute for Theory of Computing. Prior to that, he was an associate professor at Princeton and a researcher at Google Deepmind. Jason received his PhD at Stanford University advised by Trevor Hastie and Jonathan Taylor, and was a postdoctoral scholar at UC Berkeley advised by Michael Jordan. 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