Thomas Verdebout

Thomas Verdebout is a Full Professor of Statistics at Université libre de Bruxelles (ULB), Belgium. He received his PhD in Statistics from ULB in 2008 and served as an Assistant Professor at Université de Lille, France (2009–2014). His research focuses on directional statistics, high-dimensional statistics, nonparametric methods, and dimension reduction techniques. He has contributed significantly to the development of rank-based tests and optimal transport-based approaches in statistical inference.

Verdebout’s work emphasizes asymptotic theory, with notable contributions to hypothesis testing on hyperspheres, rotational symmetry analysis, and multivariate sign-based methodologies. He has held editorial roles at journals like Bernoulli and Electronic Journal of Statistics. His recent research explores the intersection of high-dimensional data analysis and nonparametric techniques, addressing challenges in spherical uniformity testing and eigenvalue-based hypothesis testing under elliptical models.

Key themes in his publications include robust statistical testing, optimality properties of directional methods, and applications of optimal transport in directional data analysis. Despite the breadth of his work, Verdebout maintains a strong focus on foundational statistical theory with practical implications for modern data analysis challenges.