AI Methodologies for Modeling and Understanding Chemical Reactivity

We leverage Artificial Intelligence (AI) to address the longstanding challenge of balancing system size, accuracy, and computational efficiency in molecular simulations.
In collaboration with French and international partners, we are developing a robust framework ArcaNN to streamline and enhance the training of deep neural networks for the investigation of chemical reactivity and complex reaction mechanisms.