Alexis Bellot



  • 2018-date: PhD Applied Mathematics and Theoretical Physics, University of Cambridge
  • 2016-2017: MSc Statistics, University of Oxford
  • 2013-2016: BSc Mathematics, Imperial College London


Alexis is a member of the Department of Applied Mathematics and Theoretical Physics Machine Learning and Artificial Intelligence research group. His current research interests revolve around developing interpretable prediction models to better understand survival patterns and variable interactions in medical patients.

Selected Publications

  • A. Bellot, M. van der Schaar, "Multitask Boosting for Survival Analysis with Competing Risks," NIPS, 2018.
  • A. Bellot, M. van der Schaar, "Boosted Trees for Risk Prognosis," Machine Learning for Healthcare Conference (MLHC), 2018.
  • A. Bellot, M. van der Schaar, "A Hierarchical Bayesian Model for Personalized Survival Predictions," IEEE J. Biomedical and Health Informatics, 2018.
  • A. Bellot, M. van der Schaar, "Tree-based Bayesian Mixture Model for Competing Risks," AISTATS, 2018.