Working on utilising machine learning for accelerating analysis of imaging data collected from fusion experiments. Specifically, I am training models on synthetic data generated via path-traced renders (using Mitsuba 2), in order to give predictions of the neutrals density, electron density and temperature distributions within the MAST vessel based on D-alpha line imaging alone.
Graduated from an MSc in Physics from Imperial College London and a BSc (Hons.) in Physics and Astrophysics from the University of Toronto. Primarily interested in rendering algorithms, optimisation techniques, machine learning and broadly systems of differential equations.