Olga Klopp
Professeur of Statistics at
ESSEC Buisness School
ESSEC Buisness School
My research lies at the intersection of mathematical statistics and machine learning. I develop statistical methods for extracting reliable information from high-dimensional, sparse, incomplete, low-rank, or complex network-structured data. My main research interests include nonparametric estimation, high-dimensional inference, sparsity, learning theory, artificial neural networks, matrix completion, graphons, and statistical network models. A central objective of my work is to design theoretically grounded methods that are relevant to modern applications, including link prediction, community detection, document classification, epidemic monitoring, graph-based learning, and the analysis of interconnected dynamical systems.
I am also actively involved in editorial work and in the organisation of international scientific programmes. My editorial appointments include serving as Associate Editor of the Annals of Statistics and Computational Statistics & Data Analysis. I previously served as Associate Editor of Bernoulli. Earlier in my career, I contributed to the organisation of the Mexican Mathematical Olympiad and served on the jury of the International Mathematical Olympiad.
I received my Habilitation à Diriger des Recherches from Université Paris Ouest Nanterre La Défense in 2016. I completed a postdoctoral fellowship at CREST and earned my PhD in Mathematics from the National Autonomous University of Mexico (UNAM). I also hold a Master’s degree in Mathematics and Applied Mathematics, awarded with honours by Lomonosov Moscow State University. My distinctions include a Fulbright Scholar Award in 2024 and a Beaufort Fellowship at St John’s College, University of Cambridge, in 2023