Per-Gunnar Martinsson

Biography

Gunnar Martinsson has been a member of the Oden Institute and a professor of mathematics at UT-Austin since 2018. Prior to joining UT, he served as a professor of mathematics at the University of Oxford. He was on the faculty at the University of Colorado, Boulder between 2005 and 2017, and prior to that he was a Gibbs assistant professor at Yale University. He completed his Ph.D. at UT-Austin in Computational and Applied Mathematics (CAM) in 2002. CAM was the Ph.D. program that preceded the current Ph.D. program administered by the Oden Institute, the Computational Sciences, Engineering, and Mathematics (CSEM) program.

He was awarded the Germund Dahlquist Prize by SIAM in 2017, elected a Fellow of SIAM in 2021, and awarded a Simons Fellowship in 2025. He is currently a visiting professor at the University of Oxford.

Dr. Martinsson’s research lies at the intersection of numerical linear algebra, scientific computing, and computational data science. A central theme of his work is randomized numerical linear algebra, which uses random sampling and embeddings to reveal and exploit structure in large matrices. He has developed fast and reliable algorithms for low-rank approximation, least-squares problems, interpolative and CUR decompositions, randomized pivoting, and Krylov methods. These techniques provide foundational computational tools for large-scale data analysis, machine learning, computational statistics, and scientific computing. A second major theme is the development of fast direct solvers and structured matrix methods for partial differential equations and integral equations, including techniques for reconstructing operators from randomized probes. This work connects classical numerical analysis and mathematical physics with modern developments in data-driven computation, including operator learning and AI.