I’m a theoretical particle physicist, working on machine learning techniques in the physical sciences.
Currently, I’m finishing my PhD at the University of Oslo, with a focus on supersymmetry and dark matter. Before that, I earned my MSc degree in physics and astronomy at the Vrije Universiteit Brussel, and worked on projects at the University of Bristol and the LHCb experiment at CERN. I’m an active member of N-PACT and the GAMBIT Collaboration.
For the past years, I have led the development of the recently published Python tool XSEC, which employs distributed Gaussian process regression techniques to accelerate the expensive predictions of high-precision supersymmetric particle production rates at the Large Hadron Collider (paper/poster).
I’m also involved in the development of Argenomic. This cheminformatics tool implements a cutting-edge illumination algorithm to achieve more efficient optimisation of small organic molecules (paper).
In my spare time, I enjoy hiking, cross-country skiing, and messing with watercolour paint.