Wenbin Zhou

Welcome!

I am a Ph.D. student (2023-) in Machine Learning and Public Policy at Carnegie Mellon University, advised by Woody Zhu. My research lies in the intersection of machine learning, statistics, and operations research. I am interested in studying algorithmics for data-driven decision-making, with a focus on three aspects: uncertainty, humans, and spatio-temporal settings. My works are motivated and applied to domains such as energy resources management, natural disasters, and other high-risk societal problems. Previously, I received my B.S. in Statistics at University of Science and Technology of China.

Recent News

• [Oct 2025] Gave three talks at the INFORMS Annual Meeting 2025, Atlanta, GA.
• [Oct 2025] Gave a talk at the CEIC Advisory Committee Meeting.
• [Sept 2025] Gave a poster presentation at the Human-AI Complementary for Decision Making workshop by NSF AI-SDM.
• [Aug 2025] Won first place in poster competition at YinzOR 2025, Pittsburgh PA.
• [May 2025] Gave a talk at the PSU-CMU energy workshop, Station College, PA.

Publications

[1] Impact of power outages on the adoption of residential solar photovoltaics in a changing climate [arXiv]
Jiashu Zhu, Wenbin Zhou, Laura Diaz Anadon, Shixiang Zhu

[2] When robustness meets conservativeness: Conformalized uncertainty calibration for balanced decision making [arXiv]
Wenbin Zhou and Shixiang Zhu

[3] Conformalized Decision Risk Assessment [arXiv] [poster] [video]
Wenbin Zhou, Agni Orfanoudaki, Shixiang Zhu

[4] Sequential Change Point Detection via Denoising Score Matching [arXiv] [code] [poster]
Wenbin Zhou, Liyan Xie, Zhigang Peng, Shixiang Zhu
Allerton Conference on Communication, Control, and Computing, 2025

[5] Hierarchical Probabilstic Conformal Prediction for Distributed Energy Adoption [arXiv] [news]
Wenbin Zhou and Shixiang Zhu
🏆 Second place, INFORMS Data Mining Best Applied Paper, 2025.
🏆 Best paper award, IEEE Power & Energy Society (awarded to short version).
Featured in AES Indiana’s 2025 Integrated Resource Plan (IRP). [IRP] [EV] [PV] [slides]

[6] Recurrent Neural Goodness-of-Fit Test for Time Series [arXiv] [poster] [code]
Aoran Zhang, Wenbin Zhou, Liyan Xie, Shixiang Zhu
International Conference on Artificial Intelligence and Statistics (AISTATS), 2025

[7] Distance-Preserving Spatial Representations in Genomic Data [arXiv] [slides] [video]
Wenbin Zhou and Jin-Hong Du
IEEE/ACM Transactions on Computational Biology and Bioinformatics

[8] Counterfactual Generative Models for Time-varying Treatments [arXiv] [poster] [code] [media]
Shenghao Wu, Wenbin Zhou, Minshuo Chen, Shixiang Zhu
ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2024
🏆 Spotlight, Deep Generative Models for Health Workshop at NeurIPS 2023.

Past News

• [Apr 2025] Gave a poster presentation at SSA Annual Meeting 2025, Baltimore, MD.
• [Oct 2024] Gave a talk and poster presentation at 2024 INFORMS Annual Meeting, Seattle WA.
• [Aug 2024] Gave an online talk on our accepted paper at BIOKDD 2024, Barcelona Spain.
• [May 2024] Joined Argonne National Laboratory as a research intern, Lemont IL.
• [Mar 2024] Served as a session co-chair for flash talks & posters at YinzOR 2024, Pittsburgh PA.
• [Aug 2023] Won first place in poster competition at YinzOR 2023, Pittsburgh PA. [media]

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