Former projects

Understanding hydrogen-bonded materials, with atomistic modeling and machine learning

Bridging length and time scales between atomic-scale phenomena and thermodynamic processes

A path integral simulation of water

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.