Biography
Yuchen Wu is an assistant professor in Cornell’s School of Operations Research and Information Engineering. Prior to Cornell, she was a postdoctoral researcher in the Department of Statistics and Data Science at the Wharton School, University of Pennsylvania. She received her Ph.D. in 2023 from the Department of Statistics at Stanford University, advised by Professor Andrea Montanari. Prior to Stanford, she received her Bachelor’s degree in Mathematics from Tsinghua University.
Her research lies at the intersection of statistics, machine learning, and game theory, with interests spanning diffusion models, high-dimensional statistics, statistical sampling, and mechanism design.
Select Publications
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Andrea Montanari, Yuchen Wu. “Fundamental limits of low-rank matrix estimation with diverging aspect ratios.” Annals of Statistics (2024).
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Yuchen Wu, Minshuo Chen, Zihao Li, Mengdi Wang, Yuting Wei. “Theoretical insights for diffusion guidance: a case study for Gaussian mixture models.” The 41st International Conference on Machine Learning (2024).
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Andrea Montanari, Yuchen Wu. “Provably efficient posterior sampling for sparse linear regression via measure decomposition.” Journal of the American Statistical Association (2025).
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Yuchen Wu, Xinyi Zhong, Zhuoran Yang. “Learning to Lead: Incentivizing Strategic Agents in the Dark.” Preprint.
Education
- B.S. in Mathematics, Tsinghua University 2018
- Ph.D. in Statistics, Stanford University 2023