Marie-Paule Cani is a Professor of Computer Science at Ecole Polytechnique. Her research interests cover both Shape Modelling and Computer Animation. She contributed over the years to a number of high level models for shapes and motion such as implicit surfaces, multi-resolution physically-based animation methods and hybrid representations for real-time natural scenes.
Following a long lasting interest for virtual sculpture, she has been recently searching for more expressive ways to create 3D contents such as combining sketch-based interfaces with procedural models based on a priori knowledge or learning. She received the Eurographics outstanding technical contributions award in 2011, a Silver medal from CNRS in 2012, and was elected at the Academia Europaea in 2013. She was awarded the ERC advanced grant EXPRESSIVE (2012-2017) and joined the ACM Siggraph Academy in 2019. She was elected at the French Academy of Sciences in 2020.
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.