AM Seminar: Column Subset Selection: Theory, Structure, and Algorithms

Presenter: Anil Damle, Associate Professor, Cornell University

Description: The column subset selection problem is a classical topic in numerical linear algebra, with renewed interest driven by applications in computational quantum chemistry, integral equations, model reduction, and model compression in machine learning. This talk surveys recent advances that clarify how structural properties of a matrix influence the performance of column selection algorithms. We focus on structure-aware and randomized methods, highlighting both theoretical guarantees and practical algorithmic consequences.

About the speaker: Anil Damle is an associate professor of computer science at Cornell University. His research focuses on the development and analysis of robust and efficient algorithms in applied and computational mathematics that exploit structure coming from underlying physical or statisical models. He interfaces with a broad range of application areas, and his work is inherently interdisciplinary—with the ultimate goal of developing algorithms that are usable for practitioners. He received his PhD from Stanford University in computational and mathematical engineering (ICME), and his MS in applied mathematics and BS in applied mathematics and computer engineering from the University of Colorado, Boulder.

This seminar is hosted by Applied Mathematics.