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I am a postdoctoral researcher at the Institute for Advanced Study. Starting July 2024, I will be an Assistant Professor of Statistics and Data Science at Yale University.
I received my B.S. in Engineering Mathematics and Statistics from the University of California, Berkeley in 2018, and my PhD in Mathematics and Statistics from the Massachusetts Institute of Technology in 2023, advised by Philippe Rigollet. In Fall 2021, I participated in the Simons Institute program on Geometric Methods in Optimization and Sampling and co-organized (with Kevin Tian) a working group on the complexity of sampling. In Spring 2022, I visited Jonathan Niles-Weed at New York University. In Summer 2022, I was a research intern at Microsoft Research, supervised by Sébastien Bubeck and Adil Salim.
I am currently writing a book on the complexity of log-concave sampling. You can read the current draft here.
Any feedback is appreciated!
Last Updated: September 29, 2023
Click here to find the notes I took during my undergraduate and graduate studies.
PhD thesis: An optimization perspective on log-concave sampling and beyond. 2023.
Here is a list of courses that I have taught in the past.
I have also been a TA for these courses.
I have led some Directed Reading Programs (DRP): 2019, 2020, 2021(A), 2021(B). I also taught a mini-course on log-concave sampling as part of a workshop on the Mathematics of Machine Learning at the Centro De Giorgi; the first video can be found here.
In 2016-2017, I won the EECS Outstanding GSI/Distinguished GSI Award.