Modelling and measuring the Universe

I like modelling and measuring.

I build statistical and machine-learning models to learn about galaxies through cosmic time, from few to many, from near to far. I always aim to have the models I build carry real physics inside them — inductive biases, geometry, and hard constraints — and to calibrate my posteriors over and over. As a modeller, I like working with the full set of the astronomical, from the instrument to the statistical inference to the theoretical models: from optimising spectrographs by understanding the atmosphere’s own emission, to geometric models of how galaxies grow inside the cosmic web.