Regular biography
Dr Jeroen Berrevoets is a Lecturer in Computer Science in the Department of Informatics at King’s College London. His research focuses on causality and machine learning, often applied to medicine. He obtained his PhD from the University of Cambridge (DAMTP). Previously, he has spent time at VUB, KU Leuven, University of Copenhagen, and BMW Group. His research interests include causality, machine learning, distributed artificial intelligence, and understanding AI in social and economic contexts.
Scholar-generated biography
Jeroen Berrevoets is a researcher at the University of Cambridge specializing in Machine Learning and Causality. His work focuses on developing methods that integrate causality into machine learning to improve the interpretability and fairness of predictive models. He has published extensively on topics such as uplift modeling, treatment effect estimation, and generative modeling for synthetic data. His research emphasizes the application of causal inference in real-world problems, including healthcare and resource allocation. Berrevoets' contributions include the development of frameworks for estimating heterogeneous treatment effects and the use of counterfactual reasoning in dynamic decision-making scenarios.