About Me
I recently received my Ph.D. in Computer Science from the Institute for Interdisciplinary Information Sciences (IIIS) at Tsinghua University, advised by Prof. Chenye Wu and Prof. Ran Duan. Before that, I was a visiting student researcher at the Computing + Mathematical Sciences (CMS) Department, Caltech from Aug. 2023 to Mar. 2024, advised by Prof. Adam Wierman. I earned my bachelor's degree in Computer Software Engineering from Huazhong University of Science & Technology in 2020. I will be joining Cornell University as a Postdoctoral Fellow in September. Contact: chenbei DOT lu AT cornell.eduResearch Interests
AI Empowers Energy; Energy Sustains AI.
My research lies at the intersection of AI and Energy, with broad interests in reinforcement learning, stochastic optimization, control, and sustainable energy systems. I focus on the theoretical and algorithmic foundations of online decision-making in large-scale networked systems, with applications in two complementary directions:
- AI for Energy: Developing learning-based optimization and control methods for the scalable, reliable, and safe operation of power grids.
- Energy for AI: Designing multi-scale scheduling algorithms to ensure the efficiency and sustainability of large-scale AI infrastructures, such as data centers.
News
- *May. 1, 2025, our work 'Overcoming the Curse of Dimensionality in Reinforcement Learning Through Approximate Factorization' has been accepted by ICML 2025. Thanks to the excellent collaborators and look forward to seeing you in Vancouver!
- *Apr. 21, 2025, our work 'Cost-Effective Closed-Loop Bilevel Robust Optimization for Joint Chance-Constrained Economic Dispatch' has been accepted by ACM e-Energy 2025 as a full paper. Thanks to the excellent collaborators and look forward to seeing you in Rotterdam!
- *Jul. 21, 2024, I'm excited to attend IEEE PESGM 2024 in Seattle, US, where I will present our work on sample-adaptive joint chance-constrained optimization for economic dispatch. Looking forward to seeing you all!
- *Jan. 1, 2024, our work 'Self-Improving Online Storage Control for Stable Wind Power Commitment' has been accepted by IEEE Transactions on Smart Grid. Thanks to the excellent collaborators!
- *Oct. 15, 2024, I'm excited to attend INFORMS 2023 in Phoenix, US. Looking forward to seeing you all!
- *Aug. 27, 2023, I begin an exciting six-month visit to the Computing + Mathematical Sciences (CMS) Department, Caltech, collaborating with Prof. Adam Wierman and many inspiring researchers!
- *Apr. 7, 2023, our work 'Sample-Adaptive Robust Economic Dispatch with Statistical Guarantees' has been accepted by IEEE Transactions on Power Systems. Thanks to the excellent collaborators!
Academic Services
Reviewers for ACC, CDC, PSCC, SmartGridComm, IEEE Transactions on Smart Grid, IEEE Transactions on Power Systems, IEEE Transactions on Industry Applications, Applied Energy, International Journal of Electrical Power & Energy Systems, IEEE Systems Journal, etc.Selected Publications
- “Overcoming the Curse of Dimensionality in Reinforcement Learning Through Approximate Factorization“
Chenbei Lu, Laixi Shi, Zaiwei Chen, Chenye Wu, Adam Wierman
ICML 2025. [pdf]- “Self-Improving Online Storage Control for Stable Wind Power Commitment“
Chenbei Lu, Hongyu Yi, Jiahao Zhang, Chenye Wu
IEEE Transactions on Smart Grid. [pdf]- “Sample-Adaptive Robust Economic Dispatch with Statistical Guarantees”
Chenbei Lu, Nan Gu, Wenqian Jiang, Chenye Wu
IEEE Transactions on Power Systems. [pdf]- “Privacy Preserving User Energy Consumption Profiling: From Theory to Application“
Chenbei Lu, Jingshi Cui, Haoxiang Wang, Hongyu Yi, Chenye Wu
IEEE Transactions on Smart Grid. [pdf] - “Self-Improving Online Storage Control for Stable Wind Power Commitment“