Hey, I’m Tom ✌️
I am currently a Research Fellow at the University of Melbourne and OzGrav.
My main research interests are in gravitational wave astrophysics and strong-field gravity.
I was previously a postdoc in computational physics at the University of Oxford where I researched reduced precision float arithmetic, stochastic methods and machine learning techniques applied to climate simulations.
I got my PhD in Theoretical Astrophysics from University College London, within the Mullard Space Science Laboratory. During this period I also spent some time at the Perimeter Institute for Theoretical Physics as Visiting Graduate Fellow.
In addition to academic research, I have spent some time doing cool stuff in applied ML and Data Science @ Mind Foundry, Revolut, Shopify and Pace.
Research
A full list of publications can be found on the arXiv or ADS
My research interests to date primarily been in relativistic astrophysics, strong-field gravity and numerical methods. I am particularly interested in the use of pulsars as high precision, multi-messenger probes of relativity in the strong field regime.
Recently I have also become interested in the application of computer science and information theory to climate modelling; the use of mixed-precision arithmetic and machine learning methods in connection with emerging hardware for exascale computation of the next-generation of climate models.
Code
In the spirit of reproducible research (see also e.g. Trisovic et al. 2022) I try, where possible, to publicly share the code associated with my published papers. Please see github for a list of all public repositories. Here are some examples of research codes:
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RelativisticDynamics.jl Differentiable, number format flexible, spin curvature dynamics.
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SpeedyWeather.jl Global atmospheric modelling for climate physics.
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ML4L. Machine learning for land surface modeling.
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Iliad. What is the timing signal from a pulsar in a strong-field relativistic environment?