Jason M. Klusowski is an Assistant Professor in the Department of Operations Research and Financial Engineering (ORFE) at Princeton University. He is also affiliated with the Center for Statistics and Machine Learning (CSML), the Princeton Laboratory for Artificial Intelligence (AI Lab), and the Princeton Language and Intelligence (PLI) initiative. His research develops statistical and algorithmic guarantees for modern large-scale predictive systems.

Before joining Princeton, Jason was an Assistant Professor in the Department of Statistics at Rutgers University–New Brunswick. He received his Ph.D. in Statistics and Data Science from Yale University.

Jason serves on the editorial board of Bernoulli, the journal of the Bernoulli Society. His research is partially supported by a Sloan Research Fellowship in Mathematics and NSF CAREER DMS-2239448, and was previously supported by NSF DMS-2054808 and TRIPODS DATA-INSPIRE Institute CCF-1934924.

Jason grew up in Winnipeg, in the heart of the Canadian Prairies. His spouse is an Assistant Professor of Marketing at Yale University.

• April 2026. Paper on coupled training with privileged information and unlabeled data with Jiahao Shi and Omar Hagrass to appear in ICML.
• April 2026. Promoted to Associate Professor with tenure, effective July 1.
• January 2026. New paper on classification imbalance as transfer learning with Eric Xia.
• December 2025. Paper on stochastic gradient descent for nonparametric additive regression with Xin Chen to appear in Bernoulli.
• November 2025. Paper on statistical-computational trade-offs for recursive adaptive partitioning estimators with Yan Shuo Tan and Krishnakumar. Balasubramanian to appear in Annals of Statistics.
• November 2025. Paper on inference with Mondrian random forests with Matias Cattaneo and William Underwood to appear in Journal of the Royal Statistical Society, Series B.