Rate My Professor Omar El Dakkak

Omar El Dakkak is an Associate Professor of Mathematics in the Department of Sciences and Engineering at Sorbonne University Abu Dhabi, School of Data, Science and Engineering. He serves as Programme Chair for the Bachelor in Mathematics, Specialisation in Data Science for Artificial Intelligence, and coordinates Artificial Intelligence projects at the university. Previously, he was Assistant Professor of Mathematics there from September 2017 to December 2018. El Dakkak holds the position of Maître de Conférences at Université Paris Nanterre since September 2009, currently on leave, affiliated with Laboratoire MODAL'X (UMR CNRS 9023). He earned his PhD in Mathematics from Université Pierre et Marie Curie (Paris VI) at Laboratoire de Statistique Théorique et Appliquée, followed by a postdoctoral position at the same institution.

His research specializations are in Discrete Probability and Empirical Processes, key to complex networks and statistical learning. He is a permanent researcher at Sorbonne University Abu Dhabi's Center for Applied Mathematics, Statistics and Data Science and Center for Artificial Intelligence and Digital Policy. Key publications include 'Exchangeable Hoeffding decompositions over finite sets: a combinatorial characterization and counterexamples' with Giovanni Peccati and Igor Prünster (Journal of Multivariate Analysis, 2014), 'Combinatorial method for bandwidth selection in wind speed kernel density estimation' with Samuel Feng et al. (IET Renewable Power Generation, 2019), 'Hoeffding decompositions and urn sequences' (2008), 'Strong approximations for the general bootstrap of empirical processes with applications in selected topics of nonparametric statistics' with Salim Bouzebda (Annales de l'ISUP, 2019), 'Limit Behavior of Sequential Empirical Measure Processes' (2012), and 'Power-law correction in the probability density function of the critical Ising magnetization' with Federico Camia and Giovanni Peccati (2025).