Research model
MixtureBetaVAE
Mixture-of-encoders β-VAE framework for interpretable latent representation learning across ophthalmic and meteorological data.
View project →Projects
Research code, scientific pipelines, and experimental builds.
A collection of current and planned projects connecting interpretable AI, medical imaging, climate data, HPC workflows, and technical prototypes.
Project index
Filter by research area or technical theme.
HPC pipeline
TC Tensor Builder
OzSTAR-ready pipeline for building tropical cyclone seed tensors from OWZ event tracks and ERA5 atmospheric fields.
View project →Medical imaging
OCT Processing
Placeholder project page for OCT-derived RNFL and GCIPL preprocessing, pairing, alignment, and model-ready dataset construction.
View project →Prototype
Agentic AI Experiments
Placeholder for experiments involving web automation, translation, structured extraction, and autonomous research workflows.
Notes coming soon →Research tooling
HPC Workflow Templates
Placeholder for reusable Slurm scripts, audit utilities, file counting tools, logging conventions, and scientific workflow patterns.
Notes coming soon →Research notes
Interactive Scientific Notebooks
Placeholder for notebooks, explainers, teaching examples, and visual walkthroughs of machine learning concepts.
View teaching →How this section will evolve
Designed to be connected to real outputs later.
Each project page currently uses placeholders for results, figures, code links, and demos. Later, these can be replaced with GitHub repositories, plots, GIFs, thesis figures, model outputs, and downloadable artifacts.
Add GitHub links
Replace placeholder links with repository URLs or private project descriptions.
Add figures
Drop in reconstruction plots, cyclone GIFs, tensor samples, and architecture diagrams.
Add results
Update metrics, ablation summaries, and real validated research findings.
Add demos
Connect latent sliders to generated images, tensors, or precomputed model outputs.
Collaboration
Building something around scientific data or interpretable AI?
I’m interested in projects that connect machine learning, research workflows, scientific visualisation, and real-world data.
Get in touch