I am an Assistant Professor of Industrial and Operations Engineering at the University of Michigan.  Combining tools from machine learning and applied probability, my research designs data-driven algorithms and provides practical insights for stochastic systems, with applications in data centers, social media platforms, and the adjudication of legal proceedings. My work has been recognized with the Public Sector OR Best Paper Award (2nd place, 2024), Service Science Best Paper in Socially Responsible Research Award (1st place), the Junior Faculty Interest Group Paper Competition (finalist, 2024), and the Applied Probability Society Best Student Paper Competition (finalist, 2022). 

I obtained my Ph.D. in EECS from MIT, where I was fortunate to be co-advised by Daniel Freund and Thodoris Lykouris. Before that, I obtained a B.E. in Computer Science in 2021 from Yao Class, Tsinghua University.

Email: wwentao (at) umich.edu

[Google scholar]     [CV (last updated: August 26)]

For students: I am looking to recruit 1–2 PhD students to join my research group. If you are interested in research involving machine learning, applied probability, optimization, algorithm design, or their intersections, please feel free to reach out.