My research (plain descriptions)

I work across a range of areas involving applying quantiative modeling to real-world systems, using mechanistic models (as a physics-based approach) as well as statistical models (e.g., using methods from machine learning). I've worked in sleep modeling, material hardness simulations, time-series analysis, machine learning, and network neuroscience. I am currently working on problems in both time-series analysis and in computational neuroscience, with the aim of discovering general principles of brain organization using a combination of statistical and physical modeling. I am based in the Complex Systems group in the School of Physics at Sydney University. If you're interested in working on time-series analysis, machine learning, or developing and applying new quantitative methods to understand the brain, I have funding available for PhD students: please throw me an email if interested. Below I've attempted to explain some of my key papers in clear, non-technical terms.

Highly comparative time-series analysis

At Comp-Engine Time Series, you can explore a library of thousands of different time-series analysis methods and tens of thousands of time-series data.

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The analysis code is available for non-commercial use:

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Music

I play cello/piano in a Melbourne band called patches. Take a listen?

Bandcamp Spotify Apple Music/iTunes (AU) Music video for our single, White Noise