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Decoding User Behaviour from Smartphone Interaction Event Streams This is my PhD thesis, it compounds my individual research over the years into one document.
Discovering Types of Smartphone Usage Sessions from User-App Interactions In this paper, we examine how embedding physical user-app activity (e.g., taps and scrolls) can provide a rich basis for summarising device usage. Using a large dataset of 82,758,449 interaction events from 86 users over an 8-week period we combine feature embedding and unsupervised learning to extract prominent interactions within clusters of smartphone usage sessions.
Utilising the co-occurrence of user interface interactions as a risk indicator for smartphone addiction The study highlights a novel methodology to transform and analyse large amounts of interaction events to infer a user's level of smartphone addiction. This is a step forward from using commonly used metrics such as pure screen on time which can misrepresent the cognitive complexities and dependencies of human behaviour.


Nintendo Switch - GBA Emulator On GitHub Utilising the restricted Nintendo Switch browser to capture input and receive streamed emulator data from a remote Python server.
Big Brain Sudokus On the App Store A Sudoku application written in React Native and managed via Expo. The free and shareable Sudokus are available in 9 difficulties.
This website On GitHub A custom built website using Astro. Includes server side rendering and a a ProseMirror powered WYSIWYG editor.
Infrared sound remote On GitHub Problem: Speakers that connect to a TV with a proprietary remote control. Solution: A infrared transceiver and a RPi + a local web server.
And much more... There is a lot of testing, prodding and half-finished bits. Feel free to visit my GitHub profile to see them.
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