Scheduled presentations:

• Neural Operator-Based Differentiable Framework for Automatic Whole-Brain Fractional Flow Reserve Estimation
  *S. Li (ShanghaiTech University), M. Hu (ShanghaiTech University), Z. Zhang (ShanghaiTech University)
• Learning Vascular Hemodynamics: Physics-Informed GNN Inference From Capillary Networks to Pulsatile Flow
  *P. Botta (Politecnico di Milano), P. Vitullo (Politecnico di Milano), F. Behrens (Politecnico di Milano), T. Ventimiglia (University of Illinois Chicago), A. Linninger (University of Illinois Chicago), L. Müller (University of Trento), P. Zunino (Politecnico di Milano)
• HyperFlow: LoRA-Modulated Implicit Neural Operator for Patient-Specific 3D Aneurysm Hemodynamics Estimation
  *M. Hu (Shanghaitech University), S. Li (Shanghaitech University), Z. Zhang (Shanghaitech University)
• What are the most influential factors in modeling aneurysmal thrombosis? A sensitivity analysis and validation study
  *Q. Liu (Xiangtan University), T. Lassila (University of Leeds), F. Lin (The University of Manchester), T. Patankar (Leeds General Infirmary), A. Sarrami-Foroushani (The University of Manchester), A. Frangi (The University of Manchester)
• Applications of the physics-informed neural network in computational mechanics
  *J. Bai (Tsingshua University), X. Feng (Tsingshua University), Y. Gu (Tsingshua University)
• A Physics-Based Digital Shadow Framework for Fast and Predictive Defect Modeling in LPBF
  *Y. Li (Dalian University of Technology), J. Guo (Northwestern University), W. Liu (Northwestern University)