As artificial intelligence becomes an increasingly powerful tool for discovering new molecules and materials, researchers are working to understand how – and in which cases – machine learning models should remain grounded in the laws of physics that govern the natural world.That challenge was the focus of the CECAM Workshop on Physics-Aware Machine Learning for Molecules and Materials, held June 1-3 at Cornell Tech in New York City and organized by Shuwen Yue, assistant professor in Cornell Duffield Engineering’s Robert F. Smith School of Chemical and Biomolecular Engineering. The event brought together approximately 80 researchers from universities, national laboratories and industry, including 28 invited speakers from the United States, Canada, the United Kingdom, Germany, Switzerland, India and Australia to explore how AI can improve the prediction of molecular behavior, accelerate materials design and drive scientific discovery while maintaining accuracy, interpretability and reliability.
Shuwen Yue, assistant professor of chemical and biomolecular engineering, organized the CECAM Workshop on Physics-Aware Machine Learning for Molecules and Materials, held June 1-3 at Cornell Tech in New York City.
