Gábor is Professor of Molecular Modelling. He is an expert in atomistic simulation, particularly in multi scale modelling that couples quantum mechanics to larger length scales. He is currently engaged in applying machine learning techniques to materials modelling problems: deriving force fields (interatomic potentials) from quantum mechanical calculations, designing similarity measures for molecules and atomic environments, predicting the binding of drug-like molecules to proteins. He is also interested in statistical problems in molecular dynamics. He is a founding editorial board member of the IOP journal Machine Learning: Science and Technology. He is an ELLIS fellow.