Dr. Matteo Sesia

Biography

Matteo Sesia is a tenured Associate Professor in the Department of Data Sciences and Operations at the USC Marshall School of Business, with a courtesy appointment in the Computer Science Department at the USC Viterbi School of Engineering. His research intersects statistics and machine learning, focusing on developing rigorous and practical methods for analyzing high-dimensional noisy data in settings where traditional modeling assumptions may not hold. Central to his work is distribution-free, model-agnostic inference, which enables reproducible variable selection and trustworthy uncertainty quantification when working alongside modern machine learning models. His methods aim to make black-box models of modern AI systems more transparent, reliable, and scientifically defensible. Professor Sesia currently serves as an Associate Editor for leading journals in statistics, including the Journal of the Royal Statistical Society (Series B) and Biometrika. He joined USC in 2020 after completing his Ph.D. in Statistics at Stanford University under the supervision of Emmanuel Candès, where he earned the Jerome H. Friedman Applied Statistics Dissertation Award for his doctoral work.

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