GEOSTAT Research team
Geometry and Statistics in acquisition data
- Leader : Hussein Yahia
- Type : Project team
- Research center(s) : Bordeaux
- Field : Applied Mathematics, Computation and Simulation
- Theme : Optimization, machine learning and statistical methods
GeoStat projecting makes fundamental and applied research on new non linear methods for the analysis of complex signals and systems, using paradigms and tools coming from statistical physics.
GeoStat's research thematics are centered on the following theoretical developments :
- Multiscale methods developped in Physics for the analysis of complex systems,
- Predictibility in complex systems,
- Multiresolution analysis,
- Analysis, classification, detection,
and the following applied objectives:
- Analysis of complex and turbulent signals in earth observation, astronomy and remote sensing,
- Digital implementation of adaptative optics in astronomy,
- Analysis of biomedical signals.
International and industrial relations
GeoStat is working in close collaboration with the following teams:
- Laboratoire d'Astrophysique de Bordeaux.
- ICM-CSIC, Department of physical oceanography, Barcelona, Spain.
- LEGOS Laboratory, UMR CNRS 5566, Toulouse, France.
- Laboratory of theoretical physics and condensed matter University Paris 6, CNRS UMR 7600, Paris, France.
- IRIT, UMR CNRS 5505, Toulouse, France.
Research teams of the same theme :
- BONUS - Big Optimization aNd Ultra-Scale Computing
- CELESTE - mathematical statistics and learning
- INOCS - INtegrated Optimization with Complex Structure
- MISTIS - Modelling and Inference of Complex and Structured Stochastic Systems
- MODAL - MOdel for Data Analysis and Learning
- RANDOPT - Randomized Optimization
- REALOPT - Reformulations based algorithms for Combinatorial Optimization
- SEQUEL - Sequential Learning
- SIERRA - Statistical Machine Learning and Parsimony
- TAU - Tackling the under-specified