Scheduled presentations:

• Physics-guided and Mechanism-inspired AI for Computational Engineering
  *S. Lee (Chung-Ang University)
• Keynote Prediction of Static Equilibria of Landau Phase Transitions using PINN
  S. Lee (UNIST), *H. Chung (UNIST)
• Identification of Non-Smooth Differential Equations Using Artificial Intelligence Methods
  *M. Adiouane (Framatome), C. Pozzolini (Framatome), C. Grenat (Framatome)
• A physics-informed neural network with built-in conservation laws for mechanical super-resolution
  *R. Dingreville (Sandia National Laboratories), V. Oommen (Brown University), A. Robertson (Sandia National Laboratories), D. Diaz (Carnegie Mellon University), C. Alleman (Sandia National Laboratories), Z. Zhang (Brown University), A. Rollett (Carnegie Mellon University), G. Karniadakis (Brown University)
• Accelerating the Quantification of Orientation Dependent Damage Caused by Voids Using Machine Learning
  *D. Montes de Oca Zapiain (Sandia National Laboratories), N. Aragon1 (Sandia National Laboratories), H. Lim (Sandia National Laboratories)
• A neural network framework for thermoviscoplasticity
  *R. Jones (Sandia National Laboratories), J. Fuhg (University of Texas at Austin), T. Seidl (Sandia National Laboratories)