Regis Duvigneau

Regis Duvigneau is a senior researcher (Directeur de Recherche) at Acumes project-team within Inria Centre at Université Côte d'Azur, and affiliated with the Jean-Alexandre Dieudonné laboratory. His work bridges scientific computing, fluid mechanics, and optimization.

• Academic Background: INRIA researcher (2016-present), Opale team (2005-2015), post-doctoral fellow at Polytechnic Montreal (2003-2004), PhD at Centrale Nantes (2000-2002)

Research focuses on numerical methods for PDE systems, particularly in fluid mechanics. Key areas: isogeometric analysis, machine learning algorithms, sensitivity analysis, Bayesian optimization, and uncertainty quantification. His recent publications demonstrate expertise in:

• Isogeometric Discontinuous Galerkin schemes for compressible flows
• Physics-Informed Neural Networks for multiphysics problems
• Statistical learning for metasurface optimization
• Shape sensitivity analysis with high-order accuracy
• Multi-objective optimization frameworks

Collaborative projects span aerodynamics, nanophotonics, and marine engineering, including ANR contracts FREEFORM (2025-2029) and FP7 initiatives.

Current advisee Nathan Ricard works on Physics-Informed Neural Networks, while past students include experts in isogeometric analysis, Bayesian optimization, and sensitivity analysis (2014-2024).