Group Testing Tutorial
Oliver Johnson, University of Bristol
Introduction to group testing and the COVID pandemic
Abstract: Group testing (pooled testing) is an efficient way of finding a small number of infected individuals in a large set, when tests are expensive or unavailable. For this reason, it has found renewed interest during the 2020-21 coronavirus pandemic. I will review the basic ideas behind the group testing problem and describe some algorithms and test strategies that have been used to solve it, in the wider context of sparse inference problems.
Bio: Oliver Johnson is Professor of Information Theory and Director of the Institute of Statistical Science in the School of Mathematics at the University of Bristol, UK. His work covers topics ranging from more theoretical results involving probabilistic limit theorems and functional inequalities to more applied work on communications and group testing. He is co-author of the survey monograph ‘Group testing: an information theory perspective’ published by Foundations and Trends in Communications and Information Theory in 2019.