ÂÜŔňÂŇÂ×

DC

David Clifton

Scientific Advisor at Sensyne Health

Professor Clifton is Professor of Clinical Machine Learning in the Department of Engineering Science of the University of Oxford. He is also a Research Fellow of the Royal Academy of Engineering.

His research focuses on the development of big data machine learning for tracking the health of complex systems. His previous research resulted in patented systems for jet engine health monitoring, used with the engines of the Airbus A380, the Boeing 787 “Dreamliner” and the Eurofighter Typhoon. Since 2008, he has translated his work into the biomedical context for healthcare applications. He has worked on Visensia, the world’s first FDA-approved multivariate patient monitoring system, and the SEND system, which is now used to monitor 20,000 patients each month in the NHS. His research has been commercialised via university spin-out companies OBS Medical, Oxehealth and Medyc, in addition to collaboration with multinational industrial bodies.

Professor Clifton’s doctorate was in information engineering, supervised by Professor Lionel Tarassenko. He spent four years as a post-doctoral researcher in biomedical engineering at the University of Oxford before his appointment to the faculty, at which point he started the Computational Health Informatics (CHI) Lab. In 2017, CHI Lab opened its second site in Suzhou, China, with support from the Chinese government, collaborating with tier-one networks of Chinese hospitals. In 2016, Professor Clifton was awarded a Grand Challenge award from the UK Engineering and Physical Sciences Research Council. He has been awarded 19 academic prizes, including the “Science, Engineering, and Technology” prize for early-career researchers. In 2018, Professor Clifton was a co-leader of the Smart Handpumps initiative from the School of Geography and the Environment and awarded the inaugural “Vice-Chancellor’s Prize for Innovation”.