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
- A hyperparameter tuning primer for Optuna and KerasTuner
- Visualising latent spaces, filters and feature maps of CNNs.
- Measuring the Sky: a two-part series on using geometry to measure distances in the solar system.
- The SHPC Retrospective: assorted topics from a postgraduate unit on scientific and high-performance computing.
- Just how many 9-dart checkouts are there?
- Procedural name generation with Markov chains
- Fractal terrains with the Diamond-Square algorithm
- 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 indielist keras linguistics longform machine learning math n-grams neural networks nlp optimisation optuna parallelism planetary science programming python quantum shpc umap vae visualisation worldbuilding
My Research
As part of my award-winning PhD research at ICRAR/UWA, I developed several AI models to classify and segment galaxy images.

These models have been applied to hundreds of thousands of galaxies across multiple datasets from large-scale observational surveys (SDSS, SAMI, COSMOS), to cosmological simulations (EAGLE), to study the evolution of galaxy morphology.

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.