Experience
A career focused on understanding exoplanets and building the methods and teams that make that work possible.
Modelling exoplanet atmospheres and planetary systems; developing machine-learning and multidimensional Bayesian methods; and investigating quantum algorithms for spectroscopic and photometric data.
CHEOPS light-curve analysis and modelling; AI algorithms for exoplanet properties and HST, JWST, and Ariel data.
Exoplanet-atmosphere modelling, machine-learning algorithms, and multidimensional Bayesian retrieval models.
Deep generative models for rapid retrieval of exoplanet-atmosphere properties.
Methods for modelling two- and three-dimensional effects in transmission spectra.
Transformer neural networks that accelerate Bayesian atmospheric retrievals.
Quantum extreme learning methods for exoplanet-atmosphere retrieval.
Thesis: Characterisation of exoplanetary atmospheres: from target selection to feature recognition using deep learning.
Thesis on orbital evolution of extrasolar giant planets.
Teaching
Supervision
I currently supervise PhD projects in atmospheric characterisation, space- and ground-based surveys, and direct imaging with machine learning.
Expertise
A toolkit designed for end-to-end computational astrophysics.
Recognition & funding
Titan V GPU for exoplanet-atmosphere research.