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Wenbin Zhou

Ph.D. Student
Carnegie Mellon University
wenbinz2 (at) andrew.cmu.edu


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 algorithms for data-driven decision-making in settings where uncertainties, spatio-temporal systems, and humans are involved. 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

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
International Conference on Learning Representations (ICLR), 2026 (short version)

[4] Sequential change point detection via denoising score matching [arXiv] [code] [poster]
Wenbin Zhou, Liyan Xie, Zhigang Peng, Shixiang Zhu
Allerton Conference on Communications, Control and Computing (short version)

[5] Hierarchical probabilstic conformal prediction for distributed energy adoption [arXiv] [news]
Wenbin Zhou and Shixiang Zhu
πŸ† Second place, INFORMS Data Mining Best Applied Paper, 2025
πŸ† Best paper award, IEEE Power & Energy Society (awarded to short version)
πŸ“ˆ 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 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
πŸ† Spotlight, Deep Generative Models for Health Workshop at NeurIPS 2023.

Past News


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