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I am an Applied Mathematics PhD candidate at the Massachusetts Institute of Technology (MIT), advised by Philippe Rigollet. From September 2023 to July 2024, I will be a postdoctoral researcher at the Institute for Advanced Study (IAS). Then, 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 University of California, Berkeley in 2018. 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 (NYU). 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: January 22, 2023
Click here to find the notes I took during my undergraduate and graduate studies.
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.
You can email me at firstname.lastname@example.org.