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Daniel Sanz-Alonso is an Associate Professor in the Department of Statistics at the University of Chicago. His academic work focuses on inverse problems, data assimilation, and the mathematical foundations of data science and machine learning. He aims to contribute to the formulation and mathematical analysis of scientific questions involving data, as well as to develop and analyze algorithms for efficient numerical simulations.
Department of Philosophy