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 nonconvex 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
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Stanford University
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Postdoc, 2019 - 2022. Mentor: Lexing Ying.
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University of Wisconsin-Madison
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Ph.D. Mathematics, 2019. Advisor: Shi Jin.
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M.S. Mathematics, 2015.
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Shanghai Jiao Tong University
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B.S. Mathematics, 2014.
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Research Interests
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Sequential Decision-Making: Continuous-time Reinforcement Learning, Multi-armed bandits.
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Optimization: Gradient-free optimization inspired by particle systems, Asynchronous-SGD, Convergence analysis for SGD.
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Uncertainty Quantification in Kinetic Equations: Sensitivity analysis, Stochastic asymptotic preserving, High-dimensional uncertainty.
My two lovely kids
