Maximilien Dreveton

Maximilien Dreveton is an Assistant Professor (Maître de Conférences) in Statistics at Université Paris Gustave-Eiffel and a member of LAMA (Laboratoire d'analyse et de mathématiques appliquées). Prior to his current position, he was a postdoctoral researcher in the INDY Lab at EPFL under the supervision of Patrick Thiran and Matthias Grossglauser. He earned his PhD in Computer Science in 2022 from Inria Sophia Antipolis with Konstantin Avrachenkov as his supervisor.

His research focuses on developing innovative algorithms and understanding the theoretical limits of identifying meaningful patterns and structures within large datasets. He has particular expertise in network analysis, community detection, and clustering. Dreveton co-authored the open-access book Statistical Analysis of Networks, which provides a comprehensive introduction to network statistical analysis covering modeling, community detection, graph-based semi-supervised learning, and network sampling.

His recent publications demonstrate a consistent focus on theoretical foundations of network analysis and community detection, with papers accepted at top venues including NeurIPS and COLT. His work on metric backbone preservation of community structure and universal lower bounds for clustering error represents significant theoretical contributions to the field. He also co-presented a tutorial on community detection at ACM SIGMETRICS / IFIP PERFORMANCE in June 2024.

Dreveton maintains an active research profile with upcoming presentations at Netsci 2025. He has developed several open-source repositories related to clustering algorithms and graph analysis, reflecting his commitment to reproducible research and community engagement.

He has also authored educational materials for mathematics preparation, including Leçons pour l'agrégation de mathématiques - Préparation à l'oral for French mathematics examination candidates.