Dr. Meng Zhang (Research Associate WP3, University of Liverpool) has just returned from the 1st AI-FLUIDs Symposium (May 27–30, 2025) held on the beautiful island of Crete, Greece — a fantastic gathering at the intersection of fluid dynamics and artificial intelligence.
Two standout keynotes were delivered by:
Prof. Petros Koumoutsakos (Harvard University), who showcased cutting-edge work using reinforcement learning for flow modeling and control, highlighting how AI can enable closed-loop regulation of complex fluid systems.
Prof. George Karniadakis (Brown University), a pioneer of Physics-Informed Neural Networks (PINNs), who discussed advanced methods for inferring hidden flow fields from sparse observations, with applications spanning inverse modeling, uncertainty quantification, and biological systems.
Beyond the keynotes, the symposium featured 200+ talks covering everything from turbulence modeling to digital twins and multi-phase flows, attracting over 500 researchers from across the globe. Even though many sessions weren’t directly focused on energy systems, they offered inspiring ideas and transferable methods.
Dr. Meng Zhang represented the Ensign team and presented her work on:
“Machine Learning-Powered Prediction Framework for Household Heating Demand” (Session 9-P.2, Day 2) – part of the ENSIGN project WP3: Heat sub Digital Twin, which explores data-driven solutions for the future of energy systems.
For more about the event: https://www.aifluids.net/
