Timothee Aubourg

Welcome to my academic homepage. I am a Postdoctoral Researcher at the Nuffield Department of Clinical Neurosciences, University of Oxford. My research sits at the intersection of data science and Digital Health Technologies, with a current focus in neurology on Parkinson’s disease.

I obtained my PhD in Health Engineering from the Université Grenoble-Alpes in 2020, jointly with Orange Labs. My doctoral work explored whether the rhythms of daily phone use could serve as a proxy for social behaviour and mental health in elderly populations. After my doctorate, I spent a year extending this to gait analysis and movement. I then joined industry as a data scientist and AI engineer for three years, working on multi-sensor fusion problems and deploying machine learning systems in production settings. Back in academia, I now try to bring these two sides together, working on Parkinson’s disease research from early exploratory analysis to validation.

Research Interests

My interests are broadly in multimodal AI and data science for health, with a particular focus on Digital Health Technologies for neurological disorders.

The question I keep returning to is measurement: what can digital tools — smartphones, wearables, neuromotor sensors, gait systems — actually tell us about disease, and how do we extract signal that is both meaningful and clinically trustworthy? This means combining passive sensing from everyday life, active clinical digital assessments, and structured clinical records. Good solutions tend to live at the junction of novel AI approaches, new data sources, and fairly classical experimental and engineering discipline, all shaped by clinical constraints. I enjoy that combination.

Equally important is keeping sight of where this needs to land: in clinical practice, not just in a paper. That requires genuine multidisciplinary alignment, which is something I value in the Oxford Parkinson’s Disease Centre. Seeing research translate into real patient benefit is what ultimately motivates this work, including through the health innovation ecosystem I am part of.

More recently I find myself drawn to agentic AI. What interests me is what it could enable in practice: faster iteration with clinicians and better handling of the unstructured complexity that multi-sensor fusion produces.

Outside research, I care about open and reproducible science and try to be involved in that community more broadly in academia.

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