Scheduled presentations:

• Bridging Scientific Machine Learning methods with physics-based models in Computational Cardiology
  F. Regazzoni*, S. Pagani, M. Salvador, L. Dede', A. Quarteroni
• Machine learning and statistical shape modelling for real-time prediction of stent deployment in realistic anatomies
  B. Bisighini*, M. Aguirre, B. Pierrat, S. Avril
• Efficient Reduced Order Modeling for Coupled Problems in Cardiac Electrophysiology
  E. Zappon*, A. Manzoni, A. Quarteroni
• Taming the Computational Burden: PBDW for Efficient State Estimation
  F. Mantegazza*, F. Caforio, E. Karabelas
• Constructive non-linear model order reduction for parametric Fluid-Structure Interaction in uncertain and moving domains.
  D. Lombardi*, M. Fernandez, S. Riffaud
• Comprehensive risk assessment of patients following type-A aortic dissection surgery: A shape analysis and machine learning approach
  J. Reddy*, T. Watanabe, T. Hayashi, H. Suito
• A non-overlapping optimization-based domain decomposition approach to component-based model reduction of incompressible flows
  L. Zhang*, T. Taddei, X. Xu