Scheduled presentations:

• Keynote What a Digital Twin Can Learn from Data, Thermodynamics, and Action Principles for Damage Assessment in Complex Materials
  *J. Chen (University ofr California San Diego), Y. Wang (University of California San Diego), S. Casebolt (University of California San Diego)
• Architecture Optimization to Stabilize and Accelerate Latent Neural Solvers for Mesoscale Materials Modeling
  *A. Robertson (Sandia National Laboratories), A. Lenau (Sandia National Laboratories), V. Oommen (Brown University), J. Shimanek (Sandia National Laboratories), R. Dingreville (Sandia National Laboratories)
• Probabilistic Diffusion-based Surrogate Model Representing Large Elasto-Plastic Deformation of Shell Structures
  *J. Heidenreich (ETH Zurich), P. Meyer (ETH Zurich), D. Mohr (ETH Zurich)
• Learning based multi-scale modeling with recurrent neural operator
  *B. Liu (University of Cambridge)
• Geometry-Enriched Token Representations for Scalable Neural Surrogates in Computational Mechanics
  *B. Alves Ribeiro (Brown University), G. Broggi (Delft University of Technology), J. Alves Ribeiro (Massachusetts Institute of Technology), M. A. Bessa (Brown University)