Resume
Academic Achievements
- Presented the paper 'Near-Optimal Regret-Queue Length Tradeoff in Online Learning for Two-Sided Markets' at NeurIPS 2025; Published 'Learning While Scheduling in Multi-Server Systems with Unknown Statistics: MaxWeight with Discounted UCB' at AISTATS 2023; Co-authored 'Exploration, Exploitation, and Engagement in Multi-Armed Bandits with Abandonment' published in the Journal of Machine Learning Research in 2024; Collaborated on an article about reinforcement learning applied to vehicle repositioning in online ride-hailing systems, published in IEEE Transactions on Intelligent Transportation Systems.
Research Experience
- Currently a postdoctoral research fellow in the Electrical Engineering and Computer Science Department at the University of Michigan, Ann Arbor.
Education
- Ph.D. from the University of Michigan, Ann Arbor, advised by Prof. Lei Ying; Master's and Bachelor's degrees from Sun Yat-sen University, Guangzhou, China.
Background
- Research interests lie in joint online learning and decision making problems, including recommendation, queueing, scheduling, matching, and pricing in unknown environments. Currently a postdoctoral research fellow at the University of Michigan, Ann Arbor.
Miscellany
- Co-authored a book titled 'Introduction to Reinforcement Learning', which includes examples and code demonstrations.