Eric Matzner-Lober

Eric Matzner-Lober is a Full Professor at University of Rennes 2, serving as a CREST Permanent Member and affiliated with the IRMAR Statistics team. He also maintains a connection with Los Alamos National Laboratory as an Affiliate Member.

His educational background includes a PhD in Applied Mathematics from Montpellier University (1997) and HDR (Habilitation à Diriger des Recherches) from Rennes University (2005).

Professor Matzner-Lober's research focuses on nonparametric estimation techniques including kernel methods and splines, machine learning approaches such as boosting and IBR, and curve analysis. His work bridges theoretical statistics with practical applications, particularly through the R programming language.

His publication record shows consistent contributions to statistical methodology, with recent work centered on iterative bias reduction techniques and regression smoothing methods. These publications demonstrate his expertise in developing computational approaches to complex statistical problems.

As an educator, he has taught various statistics courses at multiple levels including Multivariate Statistics for Geography masters programs and R software instruction for MASS (Mathématiques Appliquées, Statistiques et Sciences Sociales) students.