Computational Medicine

Our group develops computational methods to address important questions in biomedicine and healthcare. We work at the interface of engineering, data science, and medicine, in close collaboration with biomedical scientists, clinicians, and industry partners. A major focus is the analysis of retinal images to support the diagnosis of eye disease and to detect signs of wider systemic conditions. We also study how artificial intelligence tools perform in real clinical settings, with particular interest in how they can support healthcare delivery safely, reliably, and in ways that are useful to patients and professionals.

A second strand of our work examines the structure and function of blood vessels in health and disease. We use mathematical and computational models to investigate how the abnormal architecture of tumour vasculature influences the delivery of oxygen and drugs, and how this affects treatment response. We also study angiogenesis, the process by which new blood vessels form and remodel, to understand how vascular networks adapt over time.

We describe this work as Computational Medicine. For us, this is an aspirational term: it reflects the ambition to use computational methods not only to analyse data or simulate biological processes, but also to generate knowledge and tools that can make a real difference across the full spectrum of biomedicine, from basic discovery to clinical practice. It captures our aim of linking models, algorithms, imaging, and clinical evidence in ways that improve understanding of disease, support decision-making, and help translate research into patient benefit.