Scheduled presentations:

• Student Real-Time Process Monitoring Using Hybrid Methods: Set-Encoders and Physics-Informed Neural Networks
  *M. ELAARABI (Nantes Universite, IRT Jules Verne), *S. COMAS-CARDONA (Nantes Universite, Ecole Centrale Nantes), *D. BORZACCHIELLO (Nantes Universite, Ecole Centrale Nantes), *P. LE BOT (Nantes Universite, IRT Jules Verne)
• Student Physics-Informed Machine Learning for Parameter Identification on Shallow-Water Equations
  *H. Boulenc (INSA Toulouse / IMT), R. Bouclier (Institut Clement Ader (ICA) / IUF), P. Garambois (INRAE / UMR RECOVER), J. Monnier (INSA Toulouse / IMT)
• Physics-informed neural networks for solving of unsaturated groundwater flow
  *I. Đepina (NTNU), H. Gotovac (University of Split)
• Physics Informed-Neural Network for Modelling the Glucose-Insulin System in Type 1 Diabetes
  *V. Singh (Thapar Institute of Engineering and Tech.), R. Mallick (Thapar Institute of Engineering and Tech.), S. Saxena (Thapar Institute of Engineering and Tech.), D. Harusampath (Indian Institute of Science), K. Kant Mishra (Indian Institute of Science), R. Munusamy (IIITDM, Kancheepuram), A. Prasad Shrivastava (Software Technology Parks of India)
• Domain Decomposition with Bayesian Physics-Informed Neural Networks
  *J. Figueres (MELIS-UPF), *J. Vanderhaeghen (UCLouvain), K. Morozovska (KTH Royal Institute of Technology), K. Shukla (Brown University)