Scheduled presentations:

• Student Strategies for improving the performance of Physics-Informed Neural Networks for predicting flow fields in bioreactors
  *V. Travnikova (RWTH Aachen), E. von Lieres (FZ Jülich), M. Behr (RWTH Aachen)
• Student Model reduction with latent variables for discretely filtered equations
  *H. Rosenberger (Centrum Wiskunde & Informatica), B. Sanderse (Centrum Wiskunde & Informatica)
• Student Subspace-Distance-Enabled Active Learning for Non-Intrusive Reduced-Order Modeling of Parametric Fluid Flows
  *H. Kapadia (Max Planck Institute Magdeburg), L. Feng (Max Planck Institute Magdeburg), P. Benner (Max Planck Institute Magdeburg)
• Student Reduced order modeling with variational multiscale method for environmental flows
  *S. Dave (University of Calgary), A. Korobenko (University of Calgary)
• A variational Bayesian non-linear reduced order modeling in fluid dynamics
  *N. Akkari (Safran), F. Casenave (Safran)