The research activities of our team mainly focus on the development of advanced statistical and probabilistic methods for the analysis and the control of complex stochastic systems. Our approach is based on the classic triptych consisting of the following topics:
Statistical/stochastic modeling, Estimation/calibration and Control/decision
Our research within these three topics is summarized below.
Statistical and Stochastic modeling: Design and analysis of realistic and tractable sta- tistical and stochastic models, including measurement models, for complex real-life systems taking into account various random phenomena. Refined qualitative and quantitative math- ematical analysis of the stability and the robustness of statistical models and stochastic processes.
Estimation/Calibration: Theoretical methods and advanced computational methodologies to estimate the parameters and the random states of the model given partial and noisy mea- surements as well as statistical data sets. Refined mathematical analysis of the performance and the convergence of statistical and stochastic learning algorithms.
Decision and Control: Theoretical methods and advanced computational methodologies for solving regulation and stochastic optimal control problems, including optimal stopping problems and partially observed models. Refined mathematical analysis of the long time behavior and the robustness of decision and control systems. Game theory.
Inria Centre at the University of Bordeaux
In partnership with
Université de Bordeaux,Institut Polytechnique de Bordeaux,Naval Group,CNRS