Biography
I am currently building industrial ML systems. I completed my Ph.D. in ECE at UC Davis in Dec 2024, under the supervision of Prof. Lifeng Lai. My research focuses on risk-sensitive reinforcement learning (RL), enhancing algorithmic efficiency, sample complexity, and robustness.I also explored risk-sensitive RL in diverse settings, including reward-free frameworks and with human feedback (RLHF).
I received my Bachelor’s degree in Information Engineering from Zhejiang University, China, in 2019. I collaborated with Prof. Jiangtao Huangfu on integrating deep learning (DL) into medical image diagnosis and autonomous driving.
Selected work
Provably Efficient Risk-Sensitive Reinforcement Learning with Human Feedback
Online RLHF with a CVaR objective and provable efficiency guarantees.
Risk-Sensitive Reinforcement Learning with ϕ-Divergence-Risk
A policy-gradient approach for a family of risk-sensitive objectives.
Risk-Sensitive Reward-Free Reinforcement Learning with CVaR
Reward-free exploration for risk-sensitive policy learning.