PUBLIC LECTURE: Group Testing: The Mathematics of “Twenty Questions”

Please join us for a Public Lecture as part of the INFORMED AI Summer School.  In this free to attend lecture, our hub Director Sid Jaggi will present an accessible lecture describing the theory of ‘group testing’ and its wide ranging uses.

Abstract: We want to identify individuals infected with the disease in a population; however, we have limited testing resources to do so. This is an example of the classical group testing problem. Here, we must infer a (hopefully) small subset of individuals from a large population by testing groups of individuals — test outcomes are positive if the pool being tested contains at least one infected individual.

Group testing is of broad interest, with applications including item identification in RFID-tag systems, the detection of defective products in industrial settings, and big data streaming algorithms. In this talk, I’ll survey some classical bounds and algorithms for a variety of models and cutting-edge results.

Speaker Bio: Sidharth (Sid) Jaggi (B.Tech. IIT Bombay 2000, M.S./Ph.D. CalTech 2006, all in electrical engineering, post-doctoral associate MIT 2006). He joined The Chinese University of Hong Kong in 2007, and the School of Mathematics at the University of Bristol in 2020, where he is currently a Professor of Information and Coding Theory and Director of the EPSRC INFORMED-AI Hub. His research group (somewhat unwillingly) calls itself the CAN-DO-IT Team (Codes, Algorithms, Networks: Design and Optimization for Information Theory). Topics he has worked in include sparse recovery/group-testing, covert communication, network coding, and adversarial channels.

• Tuesday 17 June 2025
• School of Mathematics, Fry Building, University of Bristol – Lecture Theatre LG.02
• 3.30 – 4.30 pm 

For more information about this talk or the INFORMED AI Hub please get in touch –  informed-ai@bristol.ac.uk