I am a machine learning engineer at Splash, where I have been working on models of audio and symbolic music since 2017.

I have a background in web development, and completed my undergraduate studies in computer science at Queensland University of Technology.

I am super passionate about generative modelling, and related topics such as variational inference and neural compression. This blog is a place for me to share some of my learnings, and link to other code and projects that I am proud of.


A blog post explaining some deep generative models of piano music, which I developed at Splash in 2017-2018.
Reusable components for deep generative modelling, and a lightweight experiment runner. Written in PyTorch.
A PyTorch implementation of the bandpass convolutions described in Interpretable Convolutional Filters with SincNet.
An exercise in learning rust. Implements a few algorithms from Andrew Ng's machine learning course. (Not maintained).
Another exercise in learning rust. Implements breadth-first search, to solve a 2x2 Rubiks cube.
Work completed at Splash.