*Assistant Professor
Department of Statistics and the College*

**Daniel Sanz-Alonso’s** academic interests include data assimilation, inverse problems, machine learning, Monte Carlo methods, and uncertainty quantification. His research has been published in the *SIAM (Society for Industrial and Applied Mathematics)/ASA (American Statistical Association) Journal on Uncertainty Quantification*, the *SIAM Journal on Mathematical Analysis*, *Communications in Mathematical Sciences*, *Inverse Problems*, *Statistical Science*, and *Physica D: Nonlinear Phenomena*.

Sanz-Alonso completed a licenciatura degree in mathematics from the University of Valladolid in Spain, followed by a PhD in mathematics and statistics from the University of Warwick in the United Kingdom. Most recently, he was a postdoctoral research associate in the Division of Applied Mathematics at Brown University and a member of its Data Science Initiative.