Ruiyi Yang

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I am a Tenure-Track Associate Professor at the Institute of Natural Sciences and the School of Mathematical Sciences at Shanghai Jiao Tong University.

Previously, I was a postdoc in PACM at Princeton University under supervision of Prof. Amit Singer. 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 Bayesian computation, nonparametric statistics, and computational harmonic analysis, targeting inverse problems and machine learning applications. The overall theme of my research is to design efficient algorithms that have solid mathematical foundations.

Specifically, I have been working at the intersection of Gaussian processes and manifold learning on better modeling and computational tools for applications in statistical inverse problems. In another line of work, I study nonparametric mixture models on methodological development by drawing novel theoretical insights. I have also worked on mathematical problems arising from cryo-EM and cryo-ET.