SHORT BIOGRAPHICAL NOTE

Ioannis Kontoyiannis was born in Athens, Greece, in 1972. He is the Churchill Professor of Mathematics of Information in the Department of Pure Mathematics and Mathematical Statistics at the University of Cambridge. He is a Fellow of Darwin College, and Chair of the Faculty of Mathematics. After studying mathematics at Imperial College and Cambridge, he received his PhD in electrical engineering from Stanford University in 1998. He held academic positions at Purdue, Brown and the Athens University of Economics and Business before joining Cambridge in 2018. He is a Fellow of the IEEE and of the Institute of Mathematical Statistics, and a recipient of a Sloan Fellowship and a Marie Curie Fellowship. He has served on the editorial board of the American Mathematical Society's Quarterly of Applied Mathematics journal, Springer-Verlag's Acta Applicandae Mathematicae, the book series Lecture Notes in Mathematics by Springer-Verlag, the journal Entropy, and he was Editor-in-Chief of the IEEE Transactions on Information Theory.  

His research interests are in information theory, probability and statistics, along with their applications in data compression, neuroscience, bioinformatics, and the development of machine learning and optimization algorithms.

His work with collaborators spans the fundamental limits of compression and communication, entropy estimation, the spectral theory of Markov processes, and principled Bayesian inference. Recent research focuses on the sample complexity of data compression and channel coding, entropy inequalities and additive combinatorics, causal discovery, and stochastic algorithms for optimisation and learning. He is a co-investigator in the EPSRC-funded INFORMED-AI Hub, studying the information-theoretic foundations of distributed artificial intelligence.