Probabilities and Statistics

The research axes cover a wide range of areas in probability and statistics, both theoretical and applied.

Discrete probabilities and random structures:

• Percolation and interacting particle systems
• Algorithms and combinatorics, study of large random structures (permutations, words, paths, trees, graphs etc.)
• Stochastic geometry
• Cellular automata and discrete dynamical systems

Theory and applications of stochastic processes:

• Study of diffusion processes and link with partial differential equations
  
     –  (Multi)fractional and/or long memory processes
  
     –  Branching processes, coagulation-fragmentaition equations
• Piecewise deterministic processes
• Rough paths and regularity structures
• Stochastic partial differential equations (theoretical study and numerical analysis)
• Probabilistic numerical methods

Applied and theoretical statistics:

• High dimensional statistics and functional data analysis
• Bayesian statistics
• Spatial and spatio-temporal statistics and analysis of complex structures (networks, trees, graphs, etc)
• Statistical approaches in signal processing and image processing
• Supervised and semi-supervised learning, reinforcement learning
• Causality analysis and dependency modeling
• Time series statistics, survival analysis, time series clustering
• Applications to biology, health, natural language processing and linguistics, energy management and the environment