NeurIPS 2025, Spotlight
About
I am an Eric and Wendy Schmidt AI Postdoctoral Fellow at the AI for Science Institute, Cornell University, working with Fengqi You. I received my Ph.D. in Computer Science from the Institute for Interdisciplinary Information Sciences at Tsinghua University in 2025, advised by Chenye Wu and Ran Duan. From 2023 to 2024, I was a visiting student researcher in Computing and Mathematical Sciences at Caltech, working with Adam Wierman. I received my bachelor's degree in Computer Software Engineering from Huazhong University of Science and Technology in 2020.
Research
My research focuses on reliable and data-efficient reinforcement learning, optimization, and control for large-scale networked systems under uncertainty. I study how imperfect predictions, decomposable structure, and physical constraints can reduce what must be learned, leading to scalable algorithms with rigorous guarantees on sample complexity, performance, stability, and safety. I apply these ideas to power systems and grid-aware AI computing.
Selected Publications
Full publication list on Google ScholarNeurIPS 2026
Learning Chance-Constrained MDPs with Bellman Distributional Certificates
ICML 2025
Overcoming the Curse of Dimensionality in Reinforcement Learning Through Approximate Factorization[PDF]
IEEE Transactions on Smart Grid
Self-Improving Online Storage Control for Stable Wind Power Commitment[PDF]
IEEE Transactions on Power Systems
Sample-Adaptive Robust Economic Dispatch with Statistical Guarantees[PDF]
IEEE Control Systems Letters
On the Optimal Deterministic Policy Learning in Chance-Constrained Markov Decision Processes[PDF]
Teaching
Guest lectures
- Fall 2025: AI for Science, Cornell University
- Fall 2025: AI for Energy Systems, Cornell University
- Spring 2026: Deep Learning, Cornell University
Teaching assistance
- Fall 2021: Combinatorial Mathematics, Tsinghua University
- Fall 2022: AI Research Practice, Yao Class, Tsinghua University
News
Sep. 2026
NeurIPS 2026
Our paper Learning Chance-Constrained MDPs with Bellman Distributional Certificates was accepted.
Sep. 2025
Schmidt AI Fellowship
I joined the AI for Science Institute at Cornell University as an Eric and Wendy Schmidt AI Postdoctoral Fellow.
Sep. 2025
NeurIPS 2025 Spotlight
Our work on reinforcement learning with imperfect transition predictions was accepted as a Spotlight.
Sep. 2025
IEEE LCSS
Our work on deterministic policy learning in chance-constrained Markov decision processes was accepted.
Jul. 2025
ICML 2025
Our paper on approximate factorization for reinforcement learning was presented in Vancouver.
Apr. 2025
ACM e-Energy 2025
Our work on closed-loop bilevel robust optimization for economic dispatch was accepted.
Professional Service
Reviewer for NeurIPS, ICLR, AAAI, IEEE CDC, ACC, PSCC, IEEE SmartGridComm, ACM e-Energy, IEEE Transactions on Automatic Control, IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Smart Grid, IEEE Transactions on Power Systems, and related journals.
TPC member for IEEE SmartGridComm, ACM e-Energy poster session.