Mateo Díaz is an assistant professor in the Department of Applied Mathematics and Statistics. His interests encompass continuous optimization, computation, and statistics, with a particular focus on designing and analyzing highly effective, large-scale algorithms for applications in data science, machine learning, operations research, and signal processing.
Diaz and his team received the Beale–Orchard-Hays Prize for Excellence in Computational Mathematical Programming in 224, which recognized the team’s groundbreaking research in Primal-Dual Linear Programming.
Before his time as a postdoctoral scholar at Caltech, he received a PhD in applied mathematics and an MSc in computer science from Cornell University, mentored by Damek Davis. During his doctoral studies, he worked as a student researcher at Rappi (Colombia) and Google Research. Díaz obtained two undergraduate degrees in mathematics and in systems and computing engineering from Universidad de los Andes (Colombia).