Computational astrophysics
I build machine-learning emulators and inference tools for radiative-transfer problems in accretion outflows. The goal is to keep the physics serious while making the models fast enough to use routinely.
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Curriculum vitae
Selected research, publications, teaching, and technical work.
Thesis: Emulator-based inference of imperfect and complex astrophysical models: Reducing Millions of Computational Hours to Minutes.
First class honours with an 80% average. Final-year thesis on calibrating a new cosmological standard candle using active galactic nuclei.
Developed speculate, refined outflow diagnostics, and released a synthetic spectral library for rapid physical inference.
Worked on non-gradient optimisation in PDE solution spaces and large-scale synthetic weather data for the IBM-NASA Prithvi effort.
Built a deep-ensemble surrogate for plasma-pressure prediction that was dramatically faster and more accurate than the baseline approach.
Studied Jupiter's mass and rotational flattening while gaining observatory experience on the IAC-80, TCS, and Mons facilities.
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Technical stack
Places
A few places tied to the PhD, observatory work, industry placements, talks, and public-facing events.
A department group photo from Southampton, where most of my PhD, teaching, and day-to-day research work happens.
Night-time observatory work from my student research period with the IAC and the University of La Laguna.
From my UKAEA placement, where I worked on surrogate modelling for plasma-pressure prediction.
At the Hartree Centre during my IBM Research placement, focused on optimisation and weather-scale machine-learning workflows.
Speaking about the WRF Weather Forge and global-scale forecasting work during my IBM Research period.
A quieter point on the map tied to part-time planning and development work with Wallco alongside the PhD.
Sharing work on machine learning and scientific computing with the local data and software community.
Speaking to the wider Python and data community in London, sharing research-facing machine-learning work in a fast-paced conference setting.
Receiving the Best PhD Poster award at the SEPnet Employers Exhibition during GRADnet 2024.
A snapshot from the wider graduate-research community surrounding my PhD years in Southampton.
Presenting research in the UK Parliament during STEM for Britain, with MPs attending to engage with the work directly.
Receiving the award for Best Publication in Astrophysics.
Contact
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University of Southampton