Physical machine learning for astrophysics: differentiable spherical harmonics; harmonic Bayesian evidence; spherical scattering networks

Jason McEwen

Professor of Astrostatistics

My research interests encompass astroinformatics and astrostatistics, including Bayesian inference, harmonic analysis, optimisation, computational techniques, and machine learning and artificial intelligence, with a focus on application to cosmology and radio interferometry.