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Chen-Yu Wei is an Assistant Professor in the Computer Science department at the University of Virginia. Before, he was a Postdoctoral Associate at MIT and a Research Fellow at the Simons Institute for the Theory of Computing. 

He is broadly interested in the field of interactive machine learning. His work is centered around the following topics:

  • Robust and adaptive learning algorithms for non-stationary or adversarial environments;
  • Sample-efficient reinforcement learning algorithms with strategic exploration;
  • Decentralized multi-agent learning algorithms with efficient communication and coordination.


Ph.D. University of Southern California, 2022

M.S. National Taiwan University, 2015

B.S. National Taiwan University, 2012

Research Interests

Reinforcement Learning
Game Theory

Courses Taught

Reinforcement Learning
Algorithmic Economics


Best Paper Award, Conference on Learning Theory (COLT) 2021
Best Paper Award, Conference on Algorithmic Learning Theory (ALT) 2022
Prize for Excellence in Research with a Substantial Mathematical Component, Center for Applied Mathematical Science (CAMS), University of Southern California 2022
Simons-Berkeley Research Fellowship, Simons Institute for the Theory of Computing 2022