Scheduled presentations:

• A Reinforcement Learning Based Shock Capturing Approach for the High-Order Discontinuous Galerkin Method
  *A. Schwarz (University of Stuttgart), J. Keim (University of Stuttgart), L. Zech (University of Stuttgart), A. Beck (University of Stuttgart)
• Multi-objective training of an algebraic heat flux model to cure model-data inconsistencies in the momentum treatment
  E. Saccaggi (von Karman Institute for Fluid Dynamics), *M. Fiore (von Karman Institute for Fluid Dynamics), L. Koloszar (von Karman Institute for Fluid Dynamics), M. Mendez (von Karman Institute for Fluid Dynamics)
• Comparative assessment of optimization algorithms for kinetic model optimization
  *T. Dinelli (Politecnico di Milano), A. Stagni (Politecnico di Milano)
• Neural Network for Chemistry Closure and the Effect of Manifold Decomposition
  *T. Karpowski (STFS, TU Darmstadt), F. Ferraro (STFS, TU Darmstadt), A. Scholtissek (STFS, TU Darmstadt), C. Hasse (STFS, TU Darmstadt)
• A-posteriori Investigation of a Data-Driven Scale-Similarity Super-Resolution Model for Turbulence Closure Modeling
  *L. Nista (RWTH Aachen University), F. Froede (RWTH Aachen University), T. Grenga (University of Southampton), J. MacArt (University of Notre Dame), A. Attili (University of Edinburgh), H. Pitsch (RWTH Aachen University)
• Adaptive, Physics-based Digital Twins of Practical Combustion Systems
  *A. Procacci (Université Libre de Bruxelles), L. Donato (Université Libre de Bruxelles), C. Galletti (Unversità di Pisa), A. Coussement (Université Libre de Bruxelles), A. Parente (Université Libre de Bruxelles)