AI for Scientific Computing from Multi-Scale Modeling to Multi-Scale Pre-Training
Abstract

The rapid advancement of artificial intelligence is revolutionizing scientifc modeling, simulation, and design. This talk explores breakthroughs in AI-assisted scientific computing, highlighting the shift from multi-scale modeling to multi-scale pre-training. These pre-trained models integrate literature, simulation, and experimental data in innovative ways, further unleashing the potential of scientific computing and paving the way for the development of intelligent laboratories.

 

Speaker: Dr Linfeng ZHANG
Date: 13 September 2024 (Friday)
Time: 10:30am – 11:30am
PosterClick here

 

Biography

Dr Linfeng ZHANG, founder of DP Technology and director of AI for Science Institute, Beijing, holds a background in applied mathematics from Princeton University (2020) and physics from Peking University (2016). His work concentrates on the interdisciplinary field of AI for Science, contributing to machine learning, computational chemistry, and materials and drug design. Linfeng is the major developer of a series of popular open-source software integrating AI and physical simulation, and has been promoting the DeepModeling community for AI for Science enthusiasts. His efforts have led to several significant projects and recognition, including the ACM Gordon Bell Prize in 2020, and a feature on the cover of Forbes Asia's 30 Under 30 list for 2022.