Raoul Salle de Chou, PhD

Biography

Raoul Salle de Chou holds a PhD in applied mathematics and scientific computing, with a focus on computational modeling and machine learning for cardiovascular applications. His doctoral research investigated transport networks and myocardial perfusion through a combination of partial differential equations, optimization techniques, CFD differentiable solvers, Graph Neural Networks and synthetic vascular tree generation.

His research focuses on computational modeling, optimization, and machine learning methods for biomedical and biophysical systems. In particular, he is interested in the modeling of synthetic vascular networks and perfusion processes, with applications to cardiovascular systems. His work combines tools from physical simulation, Physics Informed Machine Learning, Graph Neural Networks and optimization. More recently, his research has explored the integration of physics-based models with data-driven approaches, including graph neural networks and hybrid learning strategies for solving perfusion in the myocardium.