Ph.D. in mathematics and machine learning, University of Grenoble Alpes, 2023
Diploma of Mathematics, ENS Paris (École normale supérieure rue d’Ulm) France, 2018

Cosme Louart is currently an Assistant Professor of the School of Data Science, CUHK-Shenzhen. He graduated from ENS Paris, received a M.Sc. on Machine learning (MVA) at ENS Paris Saclay and a Ph.D. from Grenoble university (with an affiliation to the GIPSA lab and the CEA List). He published several articles in mathematics and machine learning journals (ICML, AISTATS, IEEE, Annals of applied probability). His main contribution was the application of concentration of measure theory to study random matrices and some high dimensional data processing techniques (ELMs, GANs, robust estimation of Scatter matrices, softmax classifiers, robust linear regression...)

He worked two years in the Beijing R&D center of EDF (French electricity company) as a data engineer to provide AI solutions to energy problems.

Journal articles

1. A concentration of measure and random matrix approach to large-dimensional robust statistics C Louart, R Couillet, The Annals of Applied Probability 32 (6), 4737-4762, 4, 2022.

2. A random matrix approach to neural networks C Louart, Z Liao, R Couillet, The Annals of Applied Probability 28 (2), 2018.