The mathematical body of knowledge shared by the team members involves functional and harmonic analysis along with related fields like approximation theory, potential theory, asymptotic analysis, or system theory. Our approach is to couple these tools with constructive optimisation techniques, and to demonstrate the efficiency of such a combination in selected application areas. They concern:

• paleomagnetism in planetary sciences,
• imaging issues for functional and medical neurosciences,
• scattering issues for shape identification,
• orthopedic surgery,
• analysis of microwave devices.

The team considers inverse problems that consist in source estimation, data transmission, parameter or geometrical/shape identification issues, from available measurements. Their regularisation and resolution is performed through appropriate approximation which is consistent with the problem structure and whose error can be quantified.

We try to balance theoretical and applied work without sacrificing any, a transverse positioning made possible by the complementary skills within the team, ranging from mathematical analysis to algorithm design, numerical optimisation, prototypical software design.