DrHutan Ashrafian

Hutan Ashrafian BSc(Hons.), MBBS, PhD, MBA is a clinician scientist and surgeon who translates novel technologies and therapeutics across healthcare and health policy. He is Visiting Professor of Research Impact, Leeds University Business School. 

At Imperial College London, he is based at the Institute of Global Health Innovation (IGHI), working on real world clinical translation of artificial intelligence, digital health evaluation, and evidence generation. His work includes collaboration with Imperial, NHS partners and Google Health on artificial intelligence for breast cancer screening, and leading international reporting and quality appraisal standards for artificial intelligence diagnostic accuracy, including STARD AI and QUADAS AI.

This includes advanced statistical modelling and causal inference to large scale clinical datasets, linking multimodal data including imaging, biosignals and electronic health records to clinically meaningful endpoints. He develops and evaluates medical AI from algorithm design to trial methodology, diagnostic accuracy standards, and implementation at scale across health systems.

He integrates benchside, bedside, clinical and epidemiological data to dissect origins and develop new solutions for chronic diseases, including novel solutions to obesity and metabolic disease (ranging from novel druggable targets to bariatric-metabolic surgery). He has several eponymous medical signs named after him including the Ashrafian sign for aortic regurgitation and described his own procedure - the Ashrafian Thoracotomy.

He also serves in senior industry leadership as Chief Medical Officer at Harbinger Health (a Flagship Pioneering), supporting the development of preventive and early detection in cancer and more widely across biotechnology and digital innovation.

Alongside clinical and translational research, he publishes on long horizon questions at the interface of computation, physics, philosophy and society, including the simulation argument, temporal paradoxes and closed timelike curves, Boltzmann brains, von Neumann probes and governance concepts for advanced artificial intelligence.

Co-editor on the major reference text of Artificial Intelligence in Medicine by Springer Nature

Peer-reviewed full publications: >700, current h index=82, cited top 1% scientists worldwide.