Salim BOUZEBDA Enseignant-chercheur

Professor Salim Bouzebda earned his Ph.D. in 2007 from the Université Pierre et Marie Curie in Paris. His research portfolio spans an impressive array of topics—ranging from the treatment of censored observations and the theory of functional data to multivariate statistical methods, extreme-value theory, and bootstrap techniques—alongside pioneering applications of artificial-intelligence algorithms to the interrogation of massive datasets. To date, he has authored more than 170 peer-reviewed articles in leading international journals, a testament to his influential contributions across both theoretical and applied statistics.

In addition to his prolific publication record, Professor Bouzebda has lent his expertise to the editorial boards of distinguished periodicals, including Dependence Modeling and Communications in Statistics. He currently serves as Full Professor of Mathematical Statistics and directs the Research Laboratory in Applied Mathematics at the Université de Technologie de Compiègne, where he continues to advance the frontiers of statistical science. 

• Statistics for stochastic processes ;
• Empirical process theory ;
• U-Empirical process ;
• Bootstrap ;
• Strong invariance principle ;
• Semi/Nonparametric statistical theory ;
• Functional data analysis ;
• Multivariate analysis : Copula ;
• High dimensional probability ;
• Change point analysis ;
• Limit theorems for dependent random variables ;
• Statistical Machine Learning Theory and Applications.