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Gabriel Davis Jones

BSc (Hons), MD

Lead Researcher


My research is centered on the practical development and application of machine learning in medicine, with a particular emphasis on global health.

As a co-investigator in the MRC DPFS project "Next Generation Assessment of Fetal Wellbeing using Artificial Intelligence," I collaborate with the University of Oxford's Department of Computer Science and the Royal Women's Hospital in Melbourne, Australia. Our team manages a dataset exceeding 200,000 pregnancies, complete with clinical and biosignal data (including cardiotocography and ultrasound). Our objective is to create AI-driven tools for detecting high-risk pregnancies, focusing on complications like stillbirths and a spectrum of adverse outcomes. With our international partners, we validate our models on a diverse population, curating a dataset from various geographical and healthcare contexts. Our goal is to develop universally applicable tools to enhance maternal and newborn healthcare globally. This endeavor extends to our collaboration with Professor Jane Hirst and CareMother India, where we evaluate these models on an expansive Indian dataset.

I also lead research in the Oxford Martin School Programme on Global Epilepsy, concentrating on developing AI tools for epilepsy diagnosis and treatment in resource-limited settings, including Kenya, Ghana, Tanzania, South Africa, and India. Working with Professors Arjune Sen, Timothy Denison, and Sloan Mahone, we leverage existing big data and create software tools for data acquisition, aiming to develop culturally and geographically tailored clinical tools for regions bearing 75% of the global epilepsy burden.

My academic background includes an undergraduate degree in neuroscience, with an honours year focused on engineering rapid acquisition systems for connectomic analysis. I pursued a Doctor of Medicine (MD), with rotations at the University of California, Oxford, and Charité in Berlin. My DPhil at The Queen's College, Oxford, was supported by the Clarendon Scholarship and the Alan Turing Institute's Enrichment Scheme.

We welcome engagement from those interested in computer science, artificial intelligence, data science, medicine, and global health. Our team offers various projects and is open to inquiries from prospective collaborators.