Charles Bouveyron




Charles Bouveyron is Professor of Statistics at Université Côte d’Azur, Nice, France, and holds the Chair Inria in Data Sciences. He received in 2006 the Ph.D. degree from Université Grenoble 1 (France) for his work on high-dimensional classification. In 2006–2007, he was a postdoctoral researcher in the Department of Mathematics and Statistics of Acadia University in Canada where he worked on the statistical analysis of networks. Then, he was Assistant Professor (2007-2012) and Associate Professor (2012-2013) at Université Paris 1 Panthéon-Sorbonne. From 2013 to 2017, he was Professor of Statistics and head of Department of Statistics at Université Paris Descartes, Paris, France. His research interests include classification of high-dimensional data, classification under uncertainty and weak supervision, adaptive and online learning as well as network analysis. He has become a recognized expert in model-based classification (EM algorithm, latent variable, etc) and analysis of high-dimensional data (latent subspaces, variable selection, intrinsic dimension estimation, etc). In this context, he has developed several innovative clustering and classification methods and applied them with success in medical imaging, mass spectrometry and chemometrics.