Adam Kucharski

Biography

Dr Adam Kucharski is a mathematician, epidemiologist, and author. A Professor at the London School of Hygiene and Tropical Medicine, and as a Senior Fellow at TED, Adam specialises in the mathematics of real life and digital contagion. He reveals the patterns and predictions of how things spread. As co-founder and CTO of WholeSum, a tech startup applying hybrid AI to bring statistical rigour to analysis of text data, he also considers how decisions are made with data, and how much we should rely on artificial intelligence.

Adam has written several books which explore the science of everyday life. They include Proof: The Uncertain Science of Uncertainty, exploring how we separate truth from fiction and make better decisions in an uncertain world, drawing on real examples of misinformation to demonstrate how we can communicate more effectively. His previous book, The Rules of Contagion: Why Things Spread - and Why They Stop, considers the new rules of social contagion in an interconnected world, looking at topics including human behaviour, technology and finance. 

With both theoretical and practical approaches, Adam's expertise helps organisations handle uncertainty and make better predictions, as well as understanding why things spread - from disinformation to ideas, innovations to financial crises. Adam has led large-scale studies of social behaviour and immunity, as well as developing new ways to understand and predict outbreaks. He has contributed scientific insights to government and health agencies; been profiled by the New York Times and The Times, and collaborated on research with organisations including Meta, Space X, the BBC and the Premier League. 

Adam has also written for WIRED, The Times, the Financial Times, and is a regular voice on BBC radio and television. He has been recognised for his work with the Medical Research Council Career Development Award in Biostatistics and the Wellcome Henry Dale fellowship, as well as The Adams Prize, one of the most prestigious prizes in mathematics, for his work on epidemiological methods.