Molei Tao
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associate professor (with tenure) Office: Skiles 214A |
What do I do?
As an applied & computational mathematician, I design and apply mathematical tools from nonlinear dynamics, probability, geometry, multiscale methods, numerical analysis and computational math, and control theory to solve practical problems.
A major application I'm interested in is the theoretical and algorithmic foundation of machine learning. This includes
sampling, optimal transport, and (diffusion) generative modeling
deep learning theory, and optimization
AI4Sciences (astronomy, quantum sciences, bioengineering, scientific computing, mechanical engineering, material sciences, chemistry, …)
A subset of what I'm thankful for.
(sorry if I forget to update!)
Oct 2024: Congrats to Wei for winning a Best Poster Award at international conference “Recent Advances and Future Directions for Sampling” held at Yale!
Sep 2024: Congrats to Yuqing, Ye, Lingkai, and Zhenghao. NeurIPS’24 * 4 led by us are not too shabby as theorists.
Summer 2024: Congrats to Dr. Yuqing Wang - Ph.D. in Math! Proud of you, and best wish to your next journey as a prestigious Research Fellow at the Simon's Institute at UC Berkeley!
Summer 2024: Very grateful to have received SONY Faculty Innovation Award.
…(prehistory by ML timescale)
Interested in joining our group?
1 PhD student position is available. The currently planned area is either scientific machine learning (a.k.a. AI4Science) or deep learning theory, but exceptional candidates in other areas can also be considered. Due to the large volume of inquiries, I may not be able to reply, but I will read emails carefully. If applying, please apply to one of the following Ph.D. programs: Math, CSE, Machine Learning, ACO; choose Math as the home unit, and include my name as one of your interested faculty members. Thank you for your interest.
