Jason D. Lee

Princeton University

Associate Professor


associate professor of Electrical and Computer Engineering and Computer Science (secondary) in Princeton University and a member of the Theoretical Machine Learning Group. Previously, I was a member of the IAS and an assistant professor at USC for three years. Before that, I was a postdoc in the Computer Science Department at UC Berkeley working with Michael I. Jordan, and also collaborated with Ben Recht. I received my PhD in Applied Math advised by Trevor Hastie and Jonathan Taylor. I received a BS in Mathematics from Duke University advised by Mauro Maggioni. I am a native of Cupertino, CA.

Research Areas

Data & Information Science: Foundations of Deep Learning Representation Learning Foundations of Deep Reinforcement Learning


NSF Career Award 2022 ONR Young Investigator Award 2021 Sloan Research Fellow in Computer Science 2019 NIPS 2016 Best Student Paper Award for ‘‘Matrix Completion has no Spurious Local Minima" Finalist for Best Paper Prize for Young Researchers in Continuous Optimization Princeton Commendation for Outstanding Teaching for ELE538B ICML 2018 Workshop on Nonconvex Optimization for ML Best Paper Award for ‘‘Algorithmic Regularization in Learning Deep Homogeneous Models: Layers are Automatically Balanced"