My undergraduate studies were in pure mathematics at Ecole Normale Supérieure Paris-Saclay (formerly ENS Cachan) and at Université de Paris (formerly Paris 7 Diderot). I received a master's degree in artificial intelligence and applied mathematics from Ecole Normale Supérieure Paris-Saclay and a doctoral degree (Ph.D.) in statistics from Stanford University. After that, I took a short postdoctoral position at the Institute for Pure and Applied Mathematics and another one at the Mathematical Sciences Research Institute. I joined the University of California, San Diego as a faculty in 2005.
I mostly teach statistics courses for the Department of Mathematics. See the Planned Course Offerings for courses I am currently teaching.
I now use Canvas for all the courses I teach.
I wrote a textbook introducing probability and statistics for the "mathematically literate". It comes with a companion R notebook. (The online version of the textbook available here is in ebook format. The printed version will be published by Cambridge University Press.)
My research interests are in statistics, machine learning, and applied probability, and include (in no particular order) minimax hypothesis testing, multiple testing, clustering, dimensionality reduction, geometric inference, network analysis, signal/image denoising. With few exceptions, my papers are first posted on arxiv.org.