Jean-Pierre Minier is a researcher in the Department of Fluid Mechanics, Energy, and Environment at EDF R&D and at CEREA in Chatou, France. His research focuses on dispersed two-phase flows and stochastic modeling. He is the editor of two books: on Stochastic Methods in Fluid Mechanics (Springer, 2014) and on Particles in Wall-Bounded Turbulent Flows: Deposition, Re-Suspension, and Agglomeration (Springer, 2017) and the lead author of three review articles published in Physics Reports (2001, 2016) and Progress in Energy and Combustion Science (2015). In addition, he has co-authored several other review articles.
Martin Ferrand is the deputy head of the CEREA laboratory (Centre d'Enseignement et de Recherches en Environnement Atmosphérique), a joint venture between EDF-R&D and École des Ponts ParisTech. He teaches fluid mechanics and computational fluid dynamics (CFD) at CEREA.
Martin earned a Master of Philosophy from the University of Manchester in 2010, focusing on the Smoothed Particle Method. Since then, he has developed physical and numerical models for the open-source CFD solver, code_saturne, managing its development for five years. In 2022, he earned a PhD through validation of prior learning for his contributions to SPH and arbitrarily Eulerian-Lagrangian finite volumes. His current research explores atmospheric flows, particularly pollutant dispersion, using hybrid moment/PDF methods.
Christophe Henry is a researcher in Team Calisto at the Inria Center, Université Côte d'Azur, in Sophia Antipolis, France. He earned his PhD in 2012 from the University Pierre et Marie Curie (now Sorbonne University) and completed postdoctoral research in Gdansk, Poland, and Nice, France. In 2018, he joined the Inria Centre at Université Côte d'Azur and became a permanent researcher in 2021.
Christophe's work focuses on developing Lagrangian stochastic models for simulating dispersed two-phase flows in wall-bounded turbulent systems. His research combines fluid dynamics, interface chemistry, and surface science with numerical modeling, including stochastic methods and their implementation.
