I am a Professor within the Mullard Space Science Laboratory (MSSL) at University College London (UCL) and lead the Scientific AI (SciAI) research team.

My research interests encompass a wide range of areas across scientific AI, including physics-enhanced AI, geometric AI, statistical AI, generative AI, astrostatistics, Bayesian inference, harmonic analysis, optimisation, and computational techniques. I focus mostly on scientific problems in astrophysics but am also interested in problems in seismology, climate, medical imaging, and computer vision.

I am Founder and CEO of Copernic AI, a startup company developing geometric generative AI techniques. Try out the latest generative AI!

I also offer AI training and consulting services through Neural Learning.

I am Director of Research (Astrophysics) of UCL’s Centre for Doctoral Training (CDT) in Data Intensive Science. I am a Core Team member of the ESA Planck satellite mission, a member of the Square Kilometre Array (SKA) Science Data Processor (SDP) working group, a member of the ESA Euclid satellite Science Consortium, and a member of the Large Synoptic Survey Telescope (LSST) Dark Energy Science Collaboration (DESC) and Informatics and Statistics Science Collaboration (ISSC).

Previously I was a Royal Society Newton Fellow and before that a Leverhulme Early Career Fellow at UCL. Prior to that I was a Scientist at Ecole Polytechnique Federale de Lausanne (EPFL) and a Research Fellow of Clare College, Cambridge, after receiving a PhD from the University of Cambridge.

- Scientific AI
- Physics-enhanced AI
- Geometric AI
- Statistical AI
- Generative AI
- Astrostatistics
- Astroinformatics
- Bayesian Inference
- Harmonic Analysis
- Optimisation
- Scientific Computing

We resurrect the infamous harmonic mean estimator for computing the marginal likelihood (Bayesian evidence) and solve its problematic …

PURIFY provides functionality to perform radio interferometric imaging, i.e. to recover images from the Fourier measurements taken by …

S2FFT is a JAX package for computing Fourier transforms on the sphere and rotation group. It leverages autodiff to provide …

S2LET provides efficient routines for fast wavelet analysis of signals on the sphere. It supports both axisymmetric and directional …

S2WAV is a JAX package for computing wavelet transforms on the sphere and rotation group. It leverages autodiff to provide …

The SO3 code provides functionality to perform fast and exact Wigner transforms on the rotation group.

SOPT provides functionality to perform sparse optimisation using state-of-the-art convex optimisation algorithms.

SSHT provides functionality to perform fast and exact spin spherical harmonic transforms based on the sampling theorem on the sphere …