Jason D. Lee

Jason Lee 

Jason D. Lee
jasond+mylastname+88@gmail.com or WeChat
Google scholar and Twitter and Talk Bio.

About Me

I am an 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.

My research interests are broadly in

Students, Visitors, and Postdocs

Princeton PhD students interested in machine learning, statistics, or optimization research, please contact me; I advise students in Computer Science, Electrical Engineering, Math, ORFE, and PACM. I am recruiting PhD students and postdoctoral scholars starting in 2023 at Princeton University, please email me a CV apply.

My current focus is on machine learning with a focus on foundations of deep learning, representation learning, and deep reinforcement learning. I have lectured on the Foudations of Deep Learning at MIT Video and Slides; my tutorial at the Simons Institute: Slides and Video; and my tutorial at Machine Learning Summer School (MLSS 2021): Video and Slides.

I have also given tutorials on Representation Learning at the Johns Hopkins Winter School and Beijing AI Institute; Slides and Video.

I am also happy to host remote visitors. Summer visitors please contact me around February to schedule your visit. See a list of past visitors at here.


  • 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

Selected Publications