Scheduled presentations:

• Learning Mesh-Free Discrete Differential Operators with Self-Supervised Graph Neural Networks
  *L. Gerken Starepravo (University of Manchester), G. Fourtakas (University of Manchester), S. Lind (Cardiff University), A. Harish (University of Manchester), T. Tang (University of Manchester), J. King (University of Manchester)
• Multi-Rate Time Integration for Weakly Compressible Smoothed Particle Hydrodynamics
  *F. Thiery (Technical University of Munich), N. Adams (Technical University of Munich), S. Adami (Technical University of Munich)
• Inflow and Outflow Boundary Conditions for Blood Flow Simulations with GPU-accelerated Dissipative Particle Dynamics Solver
  *S. Tomizawa (The University of Tokyo), H. Nakajima (National Cerebral and Cardiovascular Center), Z. Li (Clemson University), Y. Hasegawa (CISS, The University of Tokyo)
• Multiscale SPH Modelling of Deformable Plastic Microfiber Aggregation in Shear Flow
  *A. Rahmat (University of Birmingham)
• Efficient Parallel Tree-based Finite Volume Particle Method
  *F. Breiden (University of Bonn), M. Schweitzer (University of Bonn)
• Why Particle-Based Models Are Uniquely Suited for Physics-Informed Machine Learning
  *A. Alexiadis (University of Birmingham)