Yuhua Zhu [CV]
Welcome!
I am a tenure-track Assistant Professor at the Department of Statistics and Data Science, UCLA.
My research focuses on the interface between partial differential equations and machine learning. I am particularly interested in using differential equations to understand and design efficient reinforcement learning and optimization algorithms.
Recruiting: Graduate students interested in reinforcement learning, interacting particle systems, and optimization for machine learning problems, please contact me.
E-mail: yuhuazhu@ucla.edu
Education
-
Stanford University
-
Postdoc, 2019 - 2022. Mentor: Lexing Ying.
-
-
University of Wisconsin-Madison
-
Ph.D. Mathematics, 2019. Advisor: Shi Jin.
-
M.S. Mathematics, 2015.
-
-
Shanghai Jiao Tong University
-
B.S. Mathematics, 2014.
-
Research Interests
-
Sequential Decision-Making: Continuous-time Reinforcement Learning, Multi-armed bandits.
-
Optimization: Gradient-free optimization inspired by particle systems, Asynchronous-SGD, Convergence analysis for SGD.
-
Uncertainty Quantification in Kinetic Equations: Sensitivity analysis, Stochastic asymptotic preserving, High-dimensional uncertainty.