My research focuses on applications of Machine Learning and statistical inference techniques to cosmology and beyond.

I combine these techniques into pipelines for the extraction of cosmological information from cutting-edge astronomical data. In particular, I focus on constraints on the “Dark Universe” from weak gravitational lensing data, as measured by optical galaxy surveys like ESA’s Euclid satellite mission.

I lead the Euclid Consortium 3x2pt Work Package and the Key Project "Euclid cosmological constraints from combined photometric probes," responsible for the headline cosmological results from Euclid weak lensing and galaxy clustering data.

I am the creator of COSMOPOWER, a Machine Learning framework for accelerated statistical inference with neural emulators.

I also like to apply advanced Machine Learning and statistical inference to interesting problems beyond cosmology and astrophysics — such as in seismology, to study earthquakes from their recorded seismic traces.

Check out my publications here.