Scheduled presentations:

• Keynote Inverse Problems in FEMU-DIC: Regularised Fields of Elastic Constants via Sparse Gaussian Process Priors
  *P. Kerfriden (Mines Paris)
• Use of physics in data-driven modeling of process-structure relationships to enhance off-the-shelf machine learning models
  *F. Bock (Helmholtz-Zentrum Hereon), N. Huber (Hamburg University of Technology), B. Klusemann (Leuphana University Lüneburg)
• Student A Data-Driven-based Homogenization Approach for Modelling the Anisotropic Damage of Quasi-brittle Heterogeneous Structures
  *Z. CHAFIA (Gustave Eiffel University), J. YVONNET (Gustave Eiffel University), J. BLEYER (Ecole des Ponts ParisTech)
• Student Adaptive Physics-Informed Digital Twin for Process Parameters Optimization
  *F. Ambrosio Garcia (KU Leuven), H. Devriendt (KU Leuven), H. Metin (Kastamonu Entegre A.S.), M. Özer (Kastamonu Entegre A.S.), F. Naets (KU Leuven)
• FNO-CG: Accelerating CG Solvers for Homogenization Problems with Fourier Neural Operators
  *J. Herb (University of Stuttgart), F. Fritzen (University of Stuttgart)