About
Artificial intelligence (AI) tools have been revolutionizing material discovery by leveraging their text-generation capabilities to interpret vast repositories of scientific data and knowledge. Through advanced pattern recognition and predictive modeling, these models sift through extensive datasets on materials properties and structures, accelerating the identification of promising candidates for further exploration. By enabling rapid screening of large databases and generating hypotheses for novel materials, foundation models serve as powerful tools for researchers, streamlining the discovery process and guiding experimental efforts towards innovative breakthroughs in material science.
- Multi-scale Modeling
- Multi-model Modeling
- Large Language Models
- Generative Modeling
- Property Prediciton
- Theory
- Machine Learning for Sampling
- Machine Learning for Interatomic Potentials
- Material Datasets
Invited Talks (In alphabetical order)
Organizers
