Ouail Zakary

My research focuses on developing machine learning-driven approaches for the atomistic modeling of molecular and solid-state systems under real physicochemical conditions. By integrating quantum mechanics at the relativistic level with classical and path integral molecular dynamics, I aim to deliver highly predictive models for structural, dynamic, and spectroscopic observables.

A significant part of my work involves training equivariant graph neural networks and kernel regression models to develop MLIPs and NMR-ML models that enable realistic simulations of complex materials.

At Aalto University, I work within the Dept. of Chemistry and Materials Science (CMAT), as well as the Otaniemi Center for Atomic-scale Materials Modeling (OCAMM), a joint unit of the computational groups of Asst. Prof. Miguel Caro, Assoc. Prof. Antti Karttunen, and Prof. Kari Laasonen, on the Business Finland project "Materials AI for accelerated industrial R&D", carried out with industrial partners in the chemistry and materials fields and with CSC. The project applies AI-driven atomistic modeling to materials structure, chemical reactions and enhanced sampling, and data-driven cheminformatics for molecular modeling and design.