Gunnar Martinsson "Randomization in computational linear algebra"

Event Type

Seminar/Symposium

Sponsor

The Siebel School of Computing and Data Science

Location

Thomas M. Siebel Center for Computer Science SC 4124

Date

Feb 14, 2025   11:00 am  

Speaker

Gunnar Martinsson, Professor, University of Texas at Austin

Contact

Kalen Mc Gowan

E-Mail

kalenmcg@illinois.edu

Phone

217-333-2383

Originating Calendar

Siebel School Speakers Calendar

Abstract:

 The talk will describe how randomized algorithms can effectively, accurately, and reliably solve important problems that arise in data analytics and large scale matrix computations. We will focus in particular on accelerated techniques for computing low rank approximations to matrices. These techniques rely on randomized embeddings that reduce the effective dimensionality of intermediate steps in the computation. The resulting algorithms are particularly well suited for processing very large data sets on modern communication constrained hardware.

While the first part of the talk serves as an overview of the field, there will also be a discussion of more recent work on a posteriori error estimation, and on techniques for computing data sparse representations of structured matrices.

Bio: 

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. He is an affiliated professor of mathematics at the Royal Institute of Technology (KTH) in Stockholm, where he also chairs the scientific advisory board of the MathDataLab.

Dr. Martinsson's research interests concern numerical analysis, scientific computing, and computational data science. His recent work has involved randomized methods in linear algebra; fast solvers for elliptic PDEs, with a particular emphasis on accelerated direct solvers; structured matrix computations; numerical methods for scattering problems, computational fluid dynamics, and acoustics; applied harmonic analysis; fast multipole methods; boundary integral equation methods; modeling of heterogeneous materials; bandgap phenomena; and lattice equations.