Talk: Prof. Sidharth Jaggi (September 01, 2022 at 4:30 PM, Zoom)

Prof. Sidharth Jaggi

University of Bristol

Meeting Details
Zoom Link: https://tum-conf.zoom.us/j/68922045363
Meeting ID: 689 2204 5363
Passcode: 461501

Abstract:

Alice wishes to communicate with Bob, but the malicious jammer James wishes to stop this communication from occurring. What can she do? In this talk I'll explore recent discoveries/capacity-characterizations in a variety of settings (the role of causality in James' jamming, the role of myopicity in his observations, the interplay between these two, and the effect of rate-limited feedback). I'll focus on one of the simplest non-trivial jamming channels -- the case of a binary input channel, in which James may erase a constant fraction of transmissions -- even here, interesting phenomena occur. Time permitting, I may also briefly describe generalizations to other jamming channels/scenarios.

Biography:

Sidharth (Sid) Jaggi received his B. Tech. from I.I.T. Bombay 2000, his M.S. and Ph.D. degrees from the CalTech in 2001 and 2006 respectively, all in EE. He spent 2006 as a Postdoctoral Associate at LIDS MIT. He joined the Department of Information Engineering at the Chinese University of Hong Kong in 2007, and the School of Mathematics at the University of Bristol in 2020, where he is now an Associate Professor. His interests lie at the intersection of network information theory, coding theory, and algorithms. His research group thus (somewhat unwillingly) calls itself the CAN-DO-IT team (Codes, Algorithms, Networks: Design and Optimization for Information Theory). Examples of topics he has dabbled in include network coding, sparse recovery/group-testing, covert communication, and his current obsession is with adversarial channels. Sidharth's research over the past 19 years has focused on an array of problems in Information and Data Sciences viewed through the lens of Information Theory, with an emphasis on both deriving fundamental performance limits and on designing algorithms approaching these fundamental limits. A particular focus is on information storage/communication/processing systems that may be under attack by eavesdropping and/or jamming malicious parties – the tools I have helped develop over the last two decades provide unconditional information-theoretic security guarantees (independent of cryptographic security guarantees often considered in security scenarios, which usually rely on computational hardness assumptions that are sometimes fragile).