One paper accepted by TMLR; served as a Conference Reviewer for UAI(2024).
Research Experience
Served as a Tutorial Teaching Assistant for STA255: Statistical Theory (Winter 2025); worked on Reheated Gradient-based Discrete Sampling for Combinatorial Optimization.
Education
Received B.S. in Statistics from Nanjing University in 2024; currently a Ph.D. student in DOSS, UofT, advised by Prof. Wenlong Mou and Prof. Xin Bing, and affiliated with the Vector Institute.
Background
Ph.D. student in Statistics at the University of Toronto, focusing on the intersection of machine learning theory, statistics, and optimization. Current research areas include Reinforcement Learning and Mean-Field Langevin Dynamics.