Eric and Wendy Schmidt AI Postdoctoral Fellow
AI for Science Institute, Cornell University
About me
I am an Eric and Wendy Schmidt AI Postdoctoral Fellow at the AI for Science Institute, Cornell University. I received my Ph.D. in Computer Science from the Institute for Interdisciplinary Information Sciences at Tsinghua University in 2025 and was a visiting student researcher in Computing and Mathematical Sciences at Caltech from 2023 to 2024. I received my bachelor's degree in Computer Software Engineering from Huazhong University of Science and Technology in 2020.
Experience
Experience
Visiting Student Researcher
Computing and Mathematical Sciences, Caltech
Research interests
Research
My research focuses on reliable and data-efficient reinforcement learning for sequential decision-making under uncertainty. I study how imperfect predictions and structural properties of the underlying system can reduce what must be learned, leading to algorithms with rigorous guarantees on sample complexity, performance, and safety. I apply these ideas to energy systems and grid-aware AI computing, where online decisions must remain reliable under changing conditions.
NeurIPS 2025, Spotlight
Reinforcement Learning with Imperfect Transition Predictions: A Bellman-Jensen Approach[PDF]
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
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
News
Sep. 2025
[Schmidt AI]
I joined the AI for Science Institute at Cornell University as an Eric and Wendy Schmidt AI Postdoctoral Fellow.
Sep. 18, 2025
[NeurIPS 2025 Spotlight]
Our work on reinforcement learning with imperfect transition predictions was accepted as a Spotlight.
Sep. 9, 2025
[IEEE LCSS]
Our work on deterministic policy learning in chance-constrained Markov decision processes was accepted.
Aug. 2025
[ICML 2025]
Our paper on approximate factorization for reinforcement learning was accepted to ICML 2025 and will be presented in Vancouver.
Apr. 21, 2025
[ACM e-Energy 2025]
Our work on closed-loop bilevel robust optimization for economic dispatch was accepted.
Dec. 2024
[CDC 2024]
Attended the IEEE Conference on Decision and Control.
Jul. 21, 2024
[IEEE PESGM 2024]
Presented our work on sample-adaptive joint chance-constrained optimization for economic dispatch in Seattle.
Jan. 1, 2024
[IEEE TSG]
Our work on self-improving online storage control for stable wind power commitment was accepted.
Oct. 2023
[INFORMS 2023]
Attended the INFORMS Annual Meeting.
Aug. 27, 2023
[Caltech CMS visit]
Began a six-month visit to Computing + Mathematical Sciences at Caltech.
Service
Professional Service
Reviewer for NeurIPS, 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.
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