I am a graduate student at Ghent University (BE), in the group of Veronique Van Speybroeck. My research interests are largely situated at the intersection of statistical mechanics, quantum mechanics, and machine learning. Specifically, I develop methods to advance the accuracy and/or efficiency of free energy calculations in both materials science and chemistry. This includes:
- leading the development of psiflow: a modular and scalable library for developing and applying ML potentials in large-scale free energy calculations (repository)
- efficient learning of symmetry-preserving collective variables (arXiv)
- reactive dynamics with ML potentials at post-HF accuracy (chemRxiv)
- smaller technical things, such as using a numerically precise extended Hessian to easily predict the mechanical properties of materials (paper), or developing and implementing a fully anisotropic energy-based pressure control algorithm in OpenMM (code).
- dimensionality reduction techniques and coarse-grained interaction potentials (slides)