- Presented a tutorial on diffusion models at ICML 2025 with Prof. Qing Qu and Prof. Liyue Shen
- Will present a tutorial on reinforcement learning at the 2025 INFORMS Annual Meetings with Prof. Yuejie Chi and Prof. Yuting Wei
- Paper on implicit regularization in nonconvex statistical estimation received the SIAM Activity Group on Imaging Science Best Paper Prize
- Paper on MagNet (an ML framework for power magnetics modeling) received the IEEE Transactions on Power Electronics Prize Paper Award (first place)
- New monograph 'Spectral Methods for Data Science: A Statistical Perspective' published in Foundations and Trends in Machine Learning
Research Experience
- Professor at the University of Pennsylvania since 2022
- Assistant Professor of Electrical and Computer Engineering at Princeton University, 2017 to 2021, and an associated faculty member of Computer Science and Applied and Computational Mathematics
Education
- Ph.D. in Electrical Engineering from Stanford University, Jan 2015
- Postdoc in Statistics at Stanford University, 2015 to 2017
Background
Currently a Professor of Statistics and Data Science, and Electrical and Systems Engineering at the University of Pennsylvania. Research interests include machine learning theory (particularly diffusion models, LLM, and RL), statistics, and optimization.
Miscellany
Looking for highly motivated postdocs and Ph.D. students with strong mathematical background and interest in machine learning theory (particularly diffusion models, LLM, and RL), statistics, and optimization.