Scheduled presentations:

• Machine Learning-Aided Inverse Design of Porous Metamaterials
  *F. Aldakheel (Leibniz Universitaet Hannover), P. THIEN NGUYEN (Leibniz Universitaet Hannover), Y. HEIDER (Leibniz Universitaet Hannover)
• On the Formulation of Data-Assisted Constitutive Models for Non-Linear Solid Mechanics
  *A. Cornejo (Universitat Politècnica de Catalunya, DECA-ETSECCPB Centre Internacional de Mètodes Numèrics a l’Enginyeria (CIMNE)), R. Rossi (Universitat Politècnica de Catalunya, DECA-ETSECCPB Centre Internacional de Mètodes Numèrics a l’Enginyeria (CIMNE))
• Surrogate Modeling of Crystal Plasticity Using Graph Neural Networks for Microstructural Design
  *A. Safi (Helmholtz-Zentrum Hereon), P. Campos (Helmholtz-Zentrum Hereon), F. Bock (Helmholtz-Zentrum Hereon), B. Klusemann (Helmholtz-Zentrum Hereon, Leuphana University)
• Multiscale modeling of metamaterials and complex composite structures using the Empirical Interscale Finite Element Method (EIFEM)
  *J. HERNÁNDEZ (CIME), E. SOUDAH (CIMNE)
• Investigation of a Machine Learning-assisted Material Point Method for Buckling Analysis
  *M. Suzuki (Keio University), M. Muramatsu (Keio University)
• AtomProNet: Data flow to and from machine learning interatomic potentials in materials science
  M. Galib (The University of British Columbia), M. Isiet (The University of British Columbia), *M. Ponga (The University of British Columbia)