• Luca Biferale (University of Tor Vergata & INFN, Italy)
    • Data driven tools for Lagrangian and Eulerian turbulence: benchmarks and challenges

  • George Karniadakis (Brown University, USA)
    • Hidden fluid mechanics

  • Koji Fukagata (Keio University, Japan)
    • Applications of convolutional neural networks to fluid mechanics problems

  • Paris Perdikaris (Microsoft / University of Pennsylvania, USA)
    • Aurora: A foundation model of the atmosphere

  • Andrea Beck (University of Stuttgart, Germany)
    • Data-driven high order schemes for compressible flows

  • Petros Koumoutsakos (Harvard University, USA)
    • Reinforcement learning for flow modeling and control

  • Sivaramakrishnan Balachandar (University of Florida, USA)
    • Scale bridging with machine learning for discovery of otherwise inaccessible multiphase physics

  • Maurizio Quadrio (Politechnico di Milano, Italy)
    • Enhancing artificial intelligence with fluid mechanics an opportunity for biomedical applications

  • Wang Yiwei (Institute of Mechanics, Chinese Academy of Sciences, China)
    • Physics-informed neural networks for phase-field method in two-phase flow: modeling and accelerating

  • Miguel Alonso Mendez (von Karman Institute for Fluid Dynamics, Belgium)
    • Scientific machine learning for digital twinning and control

  • Heinz Pitsch (RWTH Aachen University, Germany)
    • Super-resolution by generative adversarial networks for modeling intrinsic flame instabilities in turbulent hydrogen flames