General Information

[Update: The deadline for submitting the abstract is extended to 29 October]

 The workshop invites abstract submissions on any aspect of Machine Learning applied to Fluid Dynamics problems. These include, but are not limited to:
  • Data-driven/data-augmented models (e.g., rheology, turbulence modeling, combustion, multiphase, ...);
  • ML-assisted reduced-order modelling or surrogate modeling of flows, feature detection, signal processing;
  • ML-based flow control or optimization;
  • Super-resolution reconstruction of flow fields;
  • Uncertainty quantification;
  • ML-accelerated flow solvers.

Whenever possible, the authors are encouraged to use the workshop test cases to demonstrate their proposed approaches. See here for more information on those test cases.

Detailed information on the meeting are available on the workshop website: https://ml4fluids2026.github.io/

This website is uniquely used for abstract submission. After logging in, please use the "My submission" link on the left to submit your abstract for the 3rd ERCOFTAC Workshop on Machine Learning for Fluid Dynamics.
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