M3DISIM Research team
Mathematical and Mechanical Modeling with Data Interaction in Simulations for Medicine
M3DISIM (pronounced like "medicine" with a final "m") is a joint project-team with Ecole Polytechnique, part of LMS (Laboratoire de Mécanique des Solides, UMR-7649 Ecole Polytechnique - Mines ParisTech - CNRS/INSIS), and affiliated with the Inria Saclay Ile-de-France Research Center on the Ecole Polytechnique campus.
We aim at proposing novel mathematical and numerical methods and tools in the realm of the biomechanical modeling of tissues and organs, with a non-exclusive focus on the cardiovascular system. By construction, our intended contributions thus represent a multidisciplinary enterprise, at the crossroads of applied mathematics, mechanics, bioengineering, and medical applications.
- biomechanical modeling, with a particular concern for multi-scale and multi-physics phenomena;
- inverse problem methodologies, in order to benefit from the various available data to compensate for the many uncertainties inherent to such natural systems;
- numerical procedures specifically formulated and analysed to be effective for the types of direct and inverse problems considered;
- experimental studies and clinical applications, carried out both within the team and through various collaborations, in relation to the above modeling objectives.
International and industrial relations
- King's College London / St-Thomas' Hospital
- Philips Research
- University Southwestern Medical Center (UTSW), Dallas
Research teams of the same theme :
- BIOCORE - Biological control of artificial ecosystems
- CARMEN - Modélisation et calculs pour l'électrophysiologie cardiaque
- DRACULA - Multi-scale modelling of cell dynamics : application to hematopoiesis
- MAMBA - Modelling and Analysis for Medical and Biological Applications
- MONC - Mathematical modeling for Oncology
- NUMED - Numerical Medicine
- REO - Numerical simulation of biological flows
- SISTM - Statistics In System biology and Translational Medicine
- XPOP - Statistical modelling for life sciences