Matteo Sesia

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Ph.D. Candidate,
Department of Statistics,
Stanford University
Office: Sequoia 242
Email: msesia (AT) stanford (dot) edu

About me

I am a statistician who develops statistically principled and computationally efficient methodology for complex scientific problems.
During my PhD, I have worked on testing variable importance in high-dimensions, focusing on the localization of causal genetic variants and a model-agnostic feature selection method based on deep knockoffs.

Currently, I am a fifth-year Statistics Ph.D. candidate at Stanford University, advised by Emmanuel Candès.
Prior to joining Stanford, I studied Physics at Politecnico di Torino, Université Paris-Sud and the Abdus-Salam International Center for Theoretical Physics.
I also studied Statistics, Economics and Applied Mathematics at Collegio Carlo Alberto.

Curriculum Vitae.

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