Chengrui Qu

PhD Student at Caltech

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Shot in PKU, 2025 Spring

About me

I am a first-year PhD student in the Caltech Rigorous Systems Research Group, advised by Prof. Adam Wierman and Prof. Eric Mazumdar at the Computing + Mathematical Sciences (CMS) Department, California Institute of Technology. You can find my CV here. Before joining Caltech, I obtained my B.Sc. degree at Peking University.

Research interests

My research interests lie at the intersection of theoretical foundations for sequential decision-making, multi-agent systems, and the reasoning abilities of large language models, with a strong interest in real-world impact and practical applications. I’m always happy to connect—feel free to reach out if you’d like to discuss research, collaborations, or entrepreneurial opportunities. My email is cqu[at]caltech[dot]edu.

News

Jan 26, 2026 Our work “Distributionally Robust Cooperative Multi-agent Reinforcement Learning with Value Factorization” got accepted by ICLR 2026! Many Thanks to all my wonderful collaborators!
Dec 10, 2025 Happy to share our work on Decision-Dependent Distributionally Robust Optimization (DD-DRO) in Rio at CDC 2025! This work is a first step toward generalizing DRO to endogenous uncertainty, with provable guarantees.
Oct 30, 2025 Happy to give a talk on Hybrid Transfer RL in Atlanta at INFORMS 2025! I hope more researchers will investigate learning from transferred experience, beyond learning from scratch.
Sep 18, 2025 Our work “SPiDR: A Simple Approach for Zero-Shot Safety in Sim-to-Real Transfer” is accepted to NeuIPS 2025! Thanks to my wonderful collaborators!
May 05, 2025 Thrilled to share our work at AISTATS 2025! First time presenting in a ML conference!

Selected Publications

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    Hybrid Transfer Reinforcement Learning: Provable Sample Efficiency From Shifted-dynamics Data
    Chengrui Qu, Laixi Shi, Kishan Panaganti, Pengcheng You, and Adam Wierman
    AISTATS (oral, top 2%), 2025
    arXiv
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    Decision-Dependent Distributionally Robust Optimization with Application to Dynamic Pricing
    Chengrui Qu, Huiwen Jia, and Pengcheng You
    IEEE CDC, 2025
    arXiv
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    SPiDR: A Simple Approach for Zero-Shot Safety in Sim-to-Real Transfer
    Yarden As, Chengrui Qu, Benjamin Unger, Dongho Kang, Max Hart, Laixi Shi, Stelian Coros, Adam Wierman, and Andreas Krause
    NeurIPS, 2025
    arXiv
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    Distributionally Robust Cooperative Multi-Agent Reinforcement Learning via Robust Value Factorization
    Chengrui Qu, Kishan Panaganti, Christopher Yeh, and Adam Wierman
    ICLR, 2026
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    Training Generalizable Collaborative Agents via Strategic Risk Aversion
    Chengrui Qu, Yizhou Zhang, Nicolas Lanzetti, and Eric Mazumdar
    In submission to ICML, 2026
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    Understanding Agent Scaling in LLM-Based Multi-Agent Systems via Diversity
    Yingxuan Yang, Chengrui Qu, Muning Wen, Laixi Shi, Ying Wen, Weinan Zhang, Adam Wierman, and Shangding Gu
    In submission to ICML, 2026
    arXiv