Aldric Labarthe
Ph.D candidate in applied mathematics from the Ecole Normale Supérieure Paris-Saclay. My research mainly focuses on joint issues with quantitative economics (equilibrium convergence, algorithmic prices, game theory), complex systems (networks, agent-based models), geometry (graphs, hypergraphs, Riemmanian geometry and spectral geometry) and variational autoencoders with non-Euclidean priors. I am graduate program coordinator in statistics and machine learning at ENSAE Paris.