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Frederic Koehler is an Assistant Professor in the Department of Statistics at the University of Chicago. He specializes in computational learning theory and its application in various domains. He earned his PhD in Mathematics and Statistics from the Massachusetts Institute of Technology, where he was co-advised by Ankur Moitra and Elchanan Mossel. Prior to his current role, he was a Postdoctoral Fellow at Stanford University and worked as a research fellow at UC Berkeley's Simons Institute for the Program on Computational Complexity and Statistical Inference. His research focuses on topics including probability theory, high-dimensional statistics, and optimization, with particular interest in learning and inference for graphical models. He has a solid foundation in mathematical principles from his undergraduate studies at Princeton University.
Department of Philosophy