About Me

I'm currently a final-year Ph.D. candidate at the Institute for Interdisciplinary Information Sciences (IIIS), Tsinghua University, specializing in Computer Science under the guidance of Prof. Chenye Wu. I earned my bachelor's degree in Computer Software Engineering from Huazhong University of Science & Technology (HUST).


I had the opportunity to be a visiting student at the Computing + Mathematical Sciences (CMS) Department, Caltech from Aug. 2023 to Mar. 2024, advised by Prof. Adam Wierman. I also collaborate closely with Prof. Zaiwei Chen at Purdue Industrial Engineering, Prof. Wei Qi at Tsinghua Industrial Engineering, and Dr. Laixi Shi at Caltech CMS.

I am currently on the 2024-2025 job market, seeking full-time academic positions. Please feel free to reach out if there are any opportunities for collaboration or position!

Research Interests

Motivated by critical challenges in sustainable energy systems, my research interests lie at the intersection of reinforcement learning, stochastic optimization, and game theory. I focus on developing sample-efficient and robust decision-making frameworks with provable guarantees by formalizing and encoding task-dependent structures and information. Specifically, I aim to address the challenges in energy system operations within time-varying and safety-critical environments, contributing to scalable and adaptive solutions for real-world applications.

News

  • *Oct. 10, 2024, our manuscript 'Overcoming the Curse of Dimensionality in Reinforcement Learning Through Approximate Factorization' has been submitted.
  • *Jul. 21, 2024, I attended PESGM 2024, where I presented our work on sample-adaptive joint chance-constrained optimization for economic dispatch.
  • *May. 10, 2024, our manuscript 'Sample-Efficient Model-Based Reinforcement Learning Leveraging Transition Predictions' has been submitted.
  • *Jan. 1, 2024, our work 'Self-Improving Online Storage Control for Stable Wind Power Commitment' has been accepted by IEEE Transactions on Smart Grid.
  • *Aug. 27, 2023, I began 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.

Academic Services

Reviewers for ACC, CDC, PSCC, SmartGridComm, IEEE Transactions on Smart Grid, IEEE Transactions on Power Systems, IEEE Transactions on Industrial Applications, 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
    In Submission.
  • “Sample-Efficient Model-Based Reinforcement Learning Leveraging Transition Predictions“
    Chenbei Lu, Zaiwei Chen, Tongxin Li, Chenye Wu, Adam Wierman
    In Submission.
  • “Self-Improving Online Storage Control for Stable Wind Power Commitment“
    Chenbei Lu, Hongyu Yi, Jiahao Zhang, Chenye Wu
    IEEE Transactions on Smart Grid. [Link]
  • “Sample-Adaptive Robust Economic Dispatch with Statistical Guarantees”
    Chenbei Lu, Nan Gu, Wenqian Jiang, Chenye Wu
    IEEE Transactions on Power Systems. [Link]
  • “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. [Link]