Daniel Sanz-Alonso

Daniel Sanz-Alonso is a mathematician and statistician at the University of Chicago, where he is an Associate Professor in the Department of Statistics and a member of the Committee on Computational and Applied Mathematics. His research focuses on inverse problems, data assimilation, uncertainty quantification, and scientific machine learning, with an emphasis on blending complex predictive models with large data sets. He earned his PhD in Mathematics and Statistics from the University of Warwick in 2016.