Amy Zhang is an assistant professor and Texas Instruments/Kilby Fellow in the Department of Electrical and Computer Engineering at UT Austin starting Spring 2023 and an affiliate member of the Texas Robotics Consortium. Her work focuses on improving sample efficiency and generalization of reinforcement learning algorithms through bridging theory and practice, and developing new decision making algorithms for real world problems.
Amy completed her PhD in computer science at McGill University and Mila – Quebec Artificial Intelligence Institute, where she was advised by Joelle Pineau and Doina Precup. Previously, she was a research scientist at Facebook AI Research, a postdoctoral fellow at UC Berkeley, and obtained an M.Eng. in EECS and dual B.Sci. degrees in Mathematics and EECS from MIT. She also spent two years on the board of directors for Women in Machine Learning.
- Reinforcement Learning
- Representation Learning