ML Engineer | Astrophysics PhD
Welcome to my website!
Here you’ll find me (occasionally) writing about various topics I find interesting. Some featured posts include:
- Mapping galaxy morphology with VAEs
- Synthetic galaxies with GANs
- Visualising latent spaces, filters and features of CNNs.
- Just how many 9-dart checkouts are there?
- Procedural name generation with Markov chains
- Fractal terrains with the Diamond-Square algorithm
- Measuring the Sky: a two-part exploration on using geometry to measure distances in the solar system.
- The SHPC Retrospective: assorted topics from a postgraduate unit on scientific computing.
- Longform game discussions.
- Best games of the year: 2019, 2020, 2021
- Games from A to Z: 2023, 2024
or, browse by topic:
algorithms astronomy complex networks cosmology darts differential equations fortran gaming GAN geometry keras linguistics longform machine learning math n-grams neural networks nlp optimisation optuna parallelism planetary science programming python quantum shpc umap university vae visualisation worldbuilding
My Research
I completed my PhD in Astrophysics at ICRAR/UWA in 2023 developing several AI models to study the morphological evolution of galaxies.
This included several CNNs for image classification, one of the first U-Nets for segmenting spiral arms and galaxy bars into probability masks, and a transfer learning pipeline for improving the classification of high-redshift galaxies.
These models have been applied to over 100,000 galaxies across observational datasets (e.g. SDSS, COSMOS, SAMI), as well as synthetic galaxy images from cosmological simulations (EAGLE).
Preprints of my first-author papers are available on arXiv.
My PhD thesis is publicly available on UWA’s research repository.
My work was featured in an interview with Cosmos Magazine!
See my ORCID and/or Google Scholar profile for my full list of publications.