Aymeric Dieuleveut received his Ph.D. degree in mathematical statistics from École Normale Supérieure de Paris (Ulm), France, in 2017, after obtaining his MSc degree in mathematics from École Normale Supérieure de Paris in 2014.
From 2017 to 2019, he was a Research Scientist at École Polytechnique Fédérale de Lausanne. In 2019, he became Assistant Professor at École Polytechnique, Paris, France, and was named Professor in 2023.
His research topics cover high dimensional statistics, stochastic optimization, statistical machine learning, and Federate Learning. He has been working both on fundamental topics, covering algorithm design, providing theoretical guarantees and novel approaches, and on more applied topics, including collaborations with industrial partners (EDF, Owkin).
Johannes Lutzeyer is an Assistant Professor in the Data Science and Mining Team at the Computer Science Department of École Polytechnique. Previously, he completed a 2.5 year postdoc, under the supervision of Prof. Michalis Vazirgiannis, at École Polytechnique and a PhD thesis under the supervision of Prof. Andrew Walden in the Department of Mathematics at Imperial College London.
Johannes' current research focuses on Graph Neural Networks. As such, he works in the area of Graph Representation Learning in the intersection of Statistics and Computer Science.