Understanding hydrogen-bonded materials, with atomistic modeling and machine learning
Bridging length and time scales between atomic-scale phenomena and thermodynamic processes
Modeling nuclei as quantum particles, to predict the behavior of matter at finite temperature.
Looking for patterns and structure-property relations in complex materials
Modelling sophisticated experiments to understand water and interfaces.
Using machine learning to predict the properties of materials and molecules.