Rate My Professor Robin Ryder

Robin Ryder is an Associate Professor in Statistics in the Department of Mathematics at Imperial College London, where he has been appointed since 2024. Previously, he held the position of associate professor at CEREMADE, Université Paris-Dauphine from 2011 to 2024, during which he obtained his Habilitation à Diriger des Recherches in 2021. Between 2014 and 2017, Ryder served as an associate professor in the Département de Mathématiques et Applications at École Normale Supérieure. He began his postdoctoral career from 2009 to 2011 at CREST/ENSAE, working with Christian Robert, funded by GIS Sciences de la Décision and FSMP. Ryder completed his DPhil in Statistics at the University of Oxford in 2009 under the supervision of Geoff Nicholls, following participation in the Life Sciences Interface Doctoral Training Centre at Oxford from 2005 to 2006 and studies in mathematics at École Normale Supérieure from 2004 to 2005.

Ryder's research focuses on Bayesian computational statistics, with emphasis on Markov Chain Monte Carlo (MCMC) and Approximate Bayesian Computation (ABC) methods. His academic interests extend to applications in the humanities, including phylolinguistics, stochastic models for historical linguistics, and statistics for animal communication in non-human primates. Key publications include 'Approximate Bayesian Computational methods' (2012, Statistics and Computing, with Marin, Pudlo, and Robert), 'Dated language phylogenies shed light on the ancestry of Sino-Tibetan' (2019, PNAS, with Sagart et al.), 'Computational phylogenetics reveal histories of sign languages' (2024, Science, with Abner et al.), and 'Second-order Zipf’s Law for Word Co-occurrences' (2025, Open Mind, with Guerin, Steinert-Threlkeld, and Chemla). He has been awarded the Corcoran Medal for the best DPhil in Statistics at Oxford (2012) and an honorable mention for the Savage Award by the International Society for Bayesian Analysis (2010). Ryder is Chair-elect of the Bayesian Social Sciences section at ISBA, contributing to the advancement of Bayesian methods in social sciences and linguistics.