Rate My Professor Pragya Sur

Pragya Sur is an Assistant Professor of Statistics in the Department of Statistics at Harvard University, a position she has held since July 2020. She earned her Bachelor of Statistics (Honours) and Master of Statistics from the Indian Statistical Institute in Kolkata in 2012 and 2014, respectively. Sur completed her Ph.D. in Statistics at Stanford University in 2019, advised by Emmanuel J. Candès. Her dissertation, titled "A Modern Maximum Likelihood Theory for High-Dimensional Logistic Regression," received the Theodore W. Anderson Theory of Statistics Dissertation Award and the Ric Weiland Graduate Fellowship. Prior to her faculty appointment, she served as a Postdoctoral Fellow at Harvard's Center for Research on Computation and Society within the John A. Paulson School of Engineering and Applied Sciences, hosted by Cynthia Dwork from 2019 to 2020. She also held a Summer Research Internship at Microsoft Research in 2017.

Sur's research focuses on high-dimensional statistics, statistical machine learning, overparametrized problems, learning under heterogeneity and distribution shifts, and causal inference in high dimensions. Her foundational contributions bridge classical asymptotic theory with high-dimensional regimes, providing rigorous analyses of algorithms such as logistic regression, least squares, and their regularized versions, as well as boosting and interpolated classifiers. Notable publications include "A modern maximum-likelihood theory for high-dimensional logistic regression" (Proceedings of the National Academy of Sciences, 2019, with E. J. Candès), "A Precise High-Dimensional Asymptotic Theory for Boosting and Minimum-L1-Norm Interpolated Classifiers" (The Annals of Statistics, 2022, with T. Liang), "The Asymptotic Distribution of the MLE in High-dimensional Logistic Models: Arbitrary Covariance" (Bernoulli, 2022, with Q. Zhao and E. J. Candès), and "Spectrum-Aware Debiasing: A Modern Inference Framework with Applications to Principal Components Regression" (The Annals of Statistics, 2025, with Y. Li). Sur has garnered major awards, including the 2026 Alfred P. Sloan Research Fellowship in Mathematics, the 2026 IMS Thelma and Marvin Zelen Emerging Women Leaders in Data Science Award, the NSF CAREER Award (award ID: 2440824) for "High-dimensional Learning and Inference from Heterogeneous Data Sources," NSF DMS Award (award ID: 2113426), and the 2026 ASA Noether Early Career Scholar Award. She served as President of the Institute of Mathematical Statistics New Researchers Group from 2022 to 2024 and as an International Strategy Forum Asia Fellow in 2023. Sur holds editorial positions as Associate Editor for the Journal of the Royal Statistical Society Series B and Statistical Science, and as Invited Guest Co-Editor for Statistical Science’s special issue on statistics and AI. Her scholarship influences theoretical and applied communities in modern data science.