معرفی
Shixiang (Woody) Zhu is an Assistant Professor in Data Analytics at the Heinz College of Information Systems and Public Policy, Carnegie Mellon University. He holds a PhD in Machine Learning from Georgia Institute of Technology (2022) and B.S./M.S. in Computer Science from Beijing University of Posts and Telecommunications (2017). His research bridges machine learning, operations research, and statistics, focusing on sequential modeling, human-AI collaboration, and energy systems operations. He has received awards including the IEEE Power & Energy Society Best Paper Award (2025) and was a finalist for the INFORMS Wagner Prize (2021).
- Education:
- PhD in Machine Learning, Georgia Tech (2017–2022)
- B.S./M.S. in Computer Science, BUPT (2010–2017)
His research emphasizes spatio-temporal data analysis, decision making under uncertainty, and applications to energy systems, healthcare, and public policy. Notable projects include optimizing police zone design (Wagner Prize finalist) and enhancing grid resilience through robust optimization. He actively collaborates with institutions like Argonne National Laboratory and NSF-funded projects.
Awards:
- Best Paper Award, IEEE Power & Energy Society (2025)
- Gen-AI Fellows (2024)
- Finalist, INFORMS Wagner Prize (2021)
Advising & Grants:
- Advises PhD students Zekai Fan, Wenbin Zhou, and others
- Recipient of Block Center Seed Grant (2024), NSF funding (2024)
His work spans energy resilience, public policy optimization, and causal inference in social systems. He co-leads the INFORMS Data Mining Society and reviews for top journals like Operations Research and Management Science.
