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Rina Foygel Barber is a Louis Block Professor in the Department of Statistics at the University of Chicago. Her research focuses on developing and analyzing estimation and inference methods for structured high-dimensional data problems. She specializes in sparse regression, sparse nonparametric models, and low-rank models. Her work extends to the development of methods for false discovery rate control in settings with undersampled data and misspecified models, as well as distribution-free inference in situations where data distribution is unknown. In addition to her theoretical contributions, she collaborates on modeling and optimization problems related to image reconstruction and medical imaging.
Department of Philosophy