Dr Ari Ercole

Dr Ari Ercole is a Fellow in Clinical Medicine and Director of Studies in Medical Science at Magdalene College, and an Affiliated Associate Professor in the Department of Medicine. He is also faculty at the Cambridge Centre for AI in Medicine.

Alongside his academic roles, he is a consultant in intensive care medicine at Cambridge University Hospitals NHS Foundation Trust (CUH), where he is also interim Chief Clinical Information Officer. He works as a clinical informatician, focusing on artificial intelligence and digital technologies in healthcare, particularly their safe deployment to support decision-making and improve the delivery of care.

He has previously worked in prehospital emergency medicine, including helicopter emergency medical services (HEMS).

He trained in physics at the University of Cambridge, completing a PhD in condensed matter physics before retraining in medicine. His informatics work has developed from quantitative modelling of complex systems to the application of artificial intelligence in clinical and organisational settings.

Research Interests

Dr Ercole’s research focuses on artificial intelligence and data science in clinical medicine. His work examines how machine learning, large-scale health data, and digital systems can be used to support decision-making and improve patient care.

He develops data-driven methods using routinely collected healthcare data and builds agentic systems capable of reasoning over clinical information and answering healthcare questions. His research centres on prediction, monitoring, and inference from complex longitudinal data, with an emphasis on translating analytical capability into usable clinical tools.

A central theme of his work is the safe and effective deployment of AI in practice. This includes integrating systems into electronic patient records, evaluating their performance using real-world data, and understanding how they interact with clinical workflows, organisational structures, and incentives.

He is particularly interested in how AI affects productivity in healthcare, both at the level of individual clinicians and across organisations, and in the broader implications of these technologies for safety, adoption, and the delivery of care.

Qualifications

• BA
• MB
• BChir
• MA (Cantab)
• PhD

Professional Affiliations

• Fellow of the Royal College of Anaesthetists
• Fellow of the Faculty of Intensive Care Medicine
• Fellow of the British Computer Society
• Leader, UK Faculty of Digital and Innovation Professionals (FEDIP)