Pierre Wolinski is Associate Professor of Computer Science at Paris Dauphine University - PSL since September 2024. His research is in the theory of neural networks, including their optimization and regularization. He teaches in several areas of artificial intelligence, such as data analysis, machine learning, and deep learning. Previously, he did his Ph.D. on neural network pruning and hyperparameter removal, and several post-docs focused on neural network initialization and second-order optimization.

Career:

• 2016-2020: Ph.D. in Computer Science (Paris-Saclay University, Inria Saclay), supervised by Guillaume Charpiat and Yann Ollivier.
• 2020-2021: post-doc (University of Oxford), supervised by Judith Rousseau.
• 2021-2023: post-doc (Inria Grenoble-Alpes, UGA), supervised by Julyan Arbel.
• 2023-2024: post-doc (Institut de Mathématiques d'Orsay, Paris-Saclay Univ.), supervised by Gilles Blanchard and Christophe Giraud.