Ruiyi Yang

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.