- François Chapon, University of Toulouse, France
François Chapon is currently an associate professor at the Institute of Mathematics of Toulouse in University Toulouse III - Paul Sabatier. His research interests focus on probability on algebraic structures, such as random matrices and their applications, noncommutative probability, and combinatorics in relation to representation theory.
Key words: stochastic processes, random matrices, noncommutative probability.
Webpage: https://www.math.univ-toulouse.fr/~fchapon/
- Juliette Chevallier, University of Toulouse, France
Juiette Chevallier is currently Associate Professor in the Mathematics and Modeling Department (GMM) at the National Institute of Applied Sciences (INSA) of Toulouse. I conduct my research at the Institute of Mathematics of Toulouse (IMT), in the Statistics and Optimization (SO) team. In general, her research work aims at establishing mathematical models for the analysis of medical data. For this purpose, her efforts are divided into several axes, as described: Stochastic approximations-EM-LIKE Algorithms; Statistical analysis of massive and heterogeneous data; Statistical analysis of longitudinal data; The use of Riemannian geometry for the study of anatomical data.
Key words: Longitudinal data, Medical applications, Nonlinear mixed effect models, Spatio-temporal analysis, Stochastic optimization, EM-like algorithms, MCMC methods, Bayesian estimation, Applied Riemannian geometry, Massive and heterogeneous data, Variational autoencoders, Estimation under provacy constraints.
Webpage: https://juliette-chevallier.pages.math.cnrs.fr/
- Agnès Lagnoux, University of Toulouse, France
Agnès Lagnoux is currently Maître de conférence (associate professor) at the Institute of Mathematics of Toulouse (IMT) in University Toulouse II Jean-Jaurès, Toulouse, France. She has defended her PhD thesis in 2006 and her Habilitation à diriger des recherches (HDR) in 2019. She works at the interaction of probability and mathematical statistics. In particular, she's a specialist on sensitivity analysis. More recently, her research interests turn to the leverage of sensitivity analysis in machine learning. Actually, she's part of two French projects (ANR GATSBII in sensitivity analysis and cooperative game theory and ANR MBAP-P in branching processes) and one chair (ANITI - MADLADS on sensitivity analysis and machine learning).
Key words: sensitivity analysis, Gaussian processes, machine learning and artificial intelligence, large deviation theory and branching processes.
Webpage: https://perso.math.univ-toulouse.fr/lagnoux/
- Mathilde Mougeot, Paris-Saclay University and ENSIIE, France
Mathilde Mougeot is Professeur of Data science at ensIIE (link: https://www.ensiie.fr/en) and adjunct Professor at Centre Borelli (link: https://centreborelli.ens-paris-saclay.fr/en) of ENS Paris Saclay where she holds the Industrial Research Chair "Industrial Data Analytics & Machine Learning". Mathilde Mougeot's research activity is motivated by questions linked to concrete applications arising from collaborative projects with the socio-economic world. Her research focuses on scientific issues linked to predictive models in a variety of contexts, such as high dimensionality, structured data (structure at variable or observation level), data representation (feature computation), model aggregation, data frugality through model transfer (adapting a pre-calibrated model to a new task) or hybrid models (integrating knowledge from physics into models).
Key words: Data Science, Machine learning, Data Mining, Non parametric Statistics