Scheduled presentations:

• Agentic Risk-Aware Set-Based Engineering Design
  V. Kumara (Brown University), *G. Karniadakis (Brown University)
• Multi-Agent Orchestration of Optimization Workflows for Richtmyer–Meshkov Instability Studies
  *M. Fernandez-Godino (Lawrence Livermore National Laboratory), J. Belof (Lawrence Livermore National Laboratory), N. Brown (Sandia National Laboratories), B. Gunnarson (Lawrence Livermore National Laboratory), R. Hammond (Florida International University), H. Menon (Lawrence Livermore National Laboratory), Y. Li (Lawrence Livermore National Laboratory), M. Shachar (Lawrence Livermore National Laboratory), D. Sterbetz (Lawrence Livermore National Laboratory), S. Thevenin (Lawrence Livermore National Laboratory), D. White (Lawrence Livermore National Laboratory), C. Jekel (Lawrence Livermore National Laboratory), W. Schi;; (Lawrence Livermore National Laboratory)
• Optimization methods for hydrodynamic simulations using machine learning surrogate models and LLMs
  *D. Sterbentz (Lawrence Livermore National Laboratory), H. Menon (Lawrence Livermore National Laboratory), M. Shachar (Lawrence Livermore National Laboratory), S. Thevenin (Lawrence Livermore National Laboratory), W. Schill (Lawrence Livermore National Laboratory), G. Fernández-Godino (Lawrence Livermore National Laboratory), K. Korner (Lawrence Livermore National Laboratory), J. Belof (Lawrence Livermore National Laboratory), C. Jekel (Lawrence Livermore National Laboratory)
• Agentic Workflows for Optimizing Placement of Sensors for Flight Test Objects
  *G. Srinivasan (Los Alamos National Lab), C. Young (Los Alamos National Lab), S. Anderson (Los Alamos National Lab), I. Boureima (Los Alamos National Lab), K. Hodovic (Los Alamos National Lab), R. Rael (Los Alamos National Lab)
• Agentic Computer-Aided Engineering (CAE) for Model-Order Reduction (MOR)
  *D. Cadieu (The University of Texas at Dallas), J. Guo (Northwestern University), C. Park (Northwestern University), W. Liu (Northwestern University), D. Qian (The University of Texas at Dallas)
• Learning-Based Preconditioning: An LLM‑Guided Graph Spiking Neural Network Approach for a Preconditioned Conjugate Gradient Solver
  *S. Tandale (RWTH Aachen Univeristy), M. Stoffel (RWTH Aachen University)