Scheduled presentations:

• Physics-informed generative framework incorporating data importance for performance enhancement under data scarcity
  *G. Lee (KAIST), M. Lee (KAIST), I. Lee (KAIST)
• A physics-informed multi-fidelity optimization framework for constrained aerodynamic optimization of high-speed elevator
  *C. He (Yangzhou University), J. Sun (Yangzhou University), K. Izui (Kyoto University), Z. Wang (Zhejiang University), L. Qiu (Zhejiang University; CANNY elevator), S. Zhang (Zhejiang University)
• A Physics-Informed Machine Learning Framework for Aerodynamic Performance-Driven Shape Optimization
  *H. Noh (Korea Advanced Institute of Science and Techn), J. Park (Korea Advanced Institute of Science and Techn), M. Park (Korea Advanced Institute of Science and Techn), S. Lee (Korea Advanced Institute of Science and Techn)
• Physics-Informed Inverse Design of Multistable Origami with Programmable Energy Barriers
  *S. Kang (KAIST), Y. Kim (Seoul National University), J. Yang (Seoul National University), S. Ryu (KAIST)
• Rapid Inverse Design of Wire Braided Architectures Using Physics-Informed Neural Operator
  *S. Lee (Department of Mechanical Engineering, Korea A), S. Kang (Department of Mechanical Engineering, Korea A), S. Ryu (Department of Mechanical Engineering, Korea A)