Head of the team : Pierre Neuvial. Permanent members.
The scientific activity of the team is based on various themes in applied mathematics. We can distinguish the following main themes (naturally overlapping):
mathematical statistics: processes, distances and Wasserstein spaces, parametric, semi-parametric and non-parametric estimation, high-dimensional statistics, survival, extremes, mixture models, test theory and multiple tests, separation rates, functional data analysis;
statistical learning: sequential learning, massive data learning, Bayesian learning, deep learning, fairness (algorithm bias, data confidentiality), computational aspects (stochastic optimization, Monte Carlo sampling), computer experiments;
optimization: shape optimization, optimal transport, surface representation, image processing, inverse problems, optimal control, numerical optimization;
statistics for industry, biology and health (genomics, biostatistics, epidemiology): sensitivity analysis, detection of atypical regions, detection of breaks, supervised and unsupervised classification, remote sensing. Contributions cover modeling, inference, as well as methodological, algorithmic and software developments.
Many members of the team interact with other IMT teams, and more broadly with the Toulouse research ecosystem, either through ad hoc or more structured collaborations, notably via
Team Life :
The Statistics and Optimization seminar takes place every Tuesday at 11:15 am.