- Machine learning potentials for complex aqueous made2021 | Faculty of Mathematics and Physics
- Developing machine-learned potentials to simultaneously capture the dynamics of excess protons and hydroxide ions in classical and path integral simulations2023 | Faculty of Mathematics and Physics
- Reducing the Cost of Neural Network Potential Generation for Reactive Molecular Systems2023 | Faculty of Mathematics and Physics
- Constructing Collective Variables Using Invariant Learned Representations2023 | Faculty of Mathematics and Physics, Faculty of Science
- The Interplay of Structure and Dynamics in the Raman Spectrum of Liquid Water over the Full Frequency and Temperature Range2018 | Faculty of Mathematics and Physics