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Welcome to my homepage!
I am a postdoc in PACM at Princeton University
under supervision of Prof. Amit Singer .
Previously, I obtained my Ph.D. in Computational and Applied Mathematics at the University of Chicago in 2022,
advised by Prof. Daniel Sanz-Alonso, and a B.S. in Mathematics from UCLA in 2017.
My research interests lie broadly in the mathematical foundations of data science.
Specifically, my Ph.D. thesis focuses on the applications of graph-based and Gaussian process methods in statistical inverse problems and their asymptotic properties.
I also work with Prof. Bryon Aragam on nonparametric mixture models.
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