A CNRS France-Japan-Korea-Taiwan research group


    ReaDiNet(Reaction-Diffusion Network) is an International Research Network (IRN) of CNRS composed of french, japanese, korean and taiwanese researchers in the fields of mathematics and its applications in biology, ecology, medicine and chemistry. This International Research Network has started in 2020 and has been renewed in 2025. It is also the sequel to former LIA ReaDiLab and GDRI ReaDiNet projects, and hroughout its history, this project has been continuously expanding both geographically and thematically. It is part of a broader effort of INSMI (mathematical section of CNRS) to support collaborations between our four countries.

    Our scientific goal is the understanding of complex phenomena, that arise in particular in ecological and biological contexts, through the mathematical analysis of deterministic and stochastic models. Mathematics provides a deep insight on how complexity can emerge even from relatively simple systems, and conversely the life sciences have been a source for many new and challenging mathematical problems.

    Our research bears on various topics in applied mathematics such as:
    • partial differential equations: reaction-diffusion  and cross-diffusion systems, blow-up and formation of singularities, kinetic systems and mean-field models;
    • probability theory: stochastic PDEs, random walks and stochastic processes, hydrodynamic limits and statistical physics;
    • modelling in the life sciences: population dynamics, self-organization and collective behaviours, neural networks and statistics...
    We wish to bring together mathematical communities and to promote collaborations across our countries, mathematical fields and the life sciences.

                   Contact:  Thomas Giletti  thomas.giletti -at- uca.fr


Forthcoming events



      • October 20-24, 2025: IRN annual conference in Hokkaido University, Sapporo, Japan. More information to come.
      • November 25-27, 2025: Workshop in VVF Obernai, France. More information to come.