Mateo Díaz is an assistant professor in the Department of Applied Mathematics and Statistics and a member of the Mathematical Institute for Data Science and the Data Science and AI Institute. 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.
He was named a Sloan Research Fellow in 2026. In 2025, Diaz received the NSF CAREER Award. In 2024, Diaz and his team were awarded the Beale—Orchard-Hays Prize for Excellence in Computational Mathematical Programming, 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).
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Applied mathematics and statistics faculty and students help lead conversations on advancing women in artificial intelligence.
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Mateo Díaz and Soledad Villar from the Department of Applied Mathematics and Statistics are among the 126 scholars selected for the prestigious fellowship.
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Applied Mathematics and Statistics researchers will present their work spanning theoretical optimization to advanced machine learning models at NeurIPS 2025.