EECS Seminar: Low-Bandwidth Computation on Top of Error Correction

Abstract: Error correction is a fundamental tool for protecting data from noise. In this talk, I'll focus on distributed settings, and ask: What happens when we want to compute on data that is already protected with error correction? It turns out that, in some cases, we can take advantage of error correction in order to speed up or reduce the communication costs of that computation. I'll mention a few places where this comes up - including distributed storage, distributed computation and homomorphic secret sharing - and I will discuss some recent theoretical results. The talk is based on joint works with Noah Shutty, Ingerid Fosli, Victor Kolobov, Yuval Ishai and Keller Blackwell. 

Bio: Mary Wootters is an associate professor of computer science and electrical engineering at Stanford University. She received a Ph.D. in mathematics from the University of Michigan in 2014, and a B.A. in math and computer science from Swarthmore College in 2008; she was an NSF postdoctoral fellow at Carnegie Mellon University from 2014 to 2016. She works in theoretical computer science, applied math and information theory; her research interests include error correcting codes and randomized algorithms for dealing with high dimensional data. She is the recipient of an NSF CAREER award, was named a Sloan Research Fellow in 2019 and a Google Research Scholar in 2021; she was awarded the IEEE Information Theory Society James L. Massey award in 2022 and named the IEEE Information Theory Society Goldsmith Lecturer for 2024.