1. 일시 : 05월 30일 (금) 오후 4시-5시
2. 장소 : 아산이학관 526호(권택연 세미나실)
3. 연사 : 홍영준 교수님 (서울대 수리과학부)
4. 제목 : Towards Foundation Models for Scientific Machine Learning
5. 초록 : Scientific Machine Learning (SciML) has emerged as a powerful framework for solving complex scientific problems
by integrating machine learning with physical principles.
This talk will provide an overview of the theoretical foundations and practical applications of SciML, with a particular focus on leveraging
Foundation Models and In-Context Learning (ICL) in scientific domains.
Beyond solving partial differential equations (PDEs), we will explore applications in weather forecasting, metamaterials design, and more.
We will also discuss how large pre-trained models address challenges such as data scarcity,
complex boundary conditions, and physical constraints.
The talk aims to highlight how the convergence of AI and scientific computing is shaping the future of scientific discovery.