Biography
Professor David Clifton is the Royal Academy of Engineering Chair of Clinical Machine Learning at the University of Oxford, and leads the Computational Health Informatics (CHI) Lab which focuses on "AI for Healthcare". He is also NIHR Research Professor, appointed as the first non-medical scientist to the NIHR's "flagship chair".
He is OCC Fellow in AI & ML at Reuben College, a Research Fellow of the Royal Academy of Engineering, Fellow of the Alan Turing Institute, Visiting Chair in AI for Health at the University of Manchester, and a Fellow of Fudan University, China.
He studied Information Engineering at Oxford's Department of Engineering Science, supervised by Professor Lionel Tarassenko CBE. 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 focused mostly on the development of AI-based methods for healthcare. His research has been commercialised via university spin-out companies OBS Medical, Oxehealth, Biobeats, and Sensyne Health, in addition to collaboration with multinational industrial bodies.
In 2018, the CHI Lab opened its second site, in the Oxford University-owned research labs in Suzhou (China). In 2019, the Wellcome Trust's first "Flagship Centre" was announced, which joins CHI Lab to the Oxford University Clinical Research Unit in Vietnam, focused on AI for healthcare in low-income countries. In 2021, the Oxford-CityU Centre for Cardiovascular Engineering was opened in Hong Kong, of which he is co-director.
His research has won over 35 awards; he is a Grand Challenge awardee from the UK Engineering and Physical Sciences Research Council, which is an EPSRC Fellowship that provides long-term strategic support for nine "future leaders in healthcare." He was joint winner of the inaugural "Vice-Chancellor's Innovation Prize", which identifies the best interdisciplinary research across the entirety of the University of Oxford. He was the recipient of the IEEE Early Career Award in 2022, given to one engineer annually for achievements within the first ten years of their academic career.
Most Recent Publications
IMAE for noise-robust learning: mean absolute error does not treat examples equally and gradient magnitude’s variance matters
Wang X, Hua Y, Kodirov E, Clifton D & Robertson NM (2023)
An adversarial training framework for mitigating algorithmic biases in clinical machine learning.
Yang J, Soltan AAS, Eyre DW, Yang Y & Clifton DA (2023), NPJ Digit Med, 6(1), 55
Heterogeneity in diagnosis and prognosis of ischaemic stroke subtypes: 9-year follow-up of 22000 cases in Chinese adults.
Chun M, Qin H, Turnbull I, Sansome S, Gilbert S et al. (2023), Int J Stroke, 17474930231162265
On the Effectiveness of Compact Biomedical Transformers.
Rohanian O, Nouriborji M, Kouchaki S & Clifton DA (2023), Bioinformatics
SeroTracker-RoB: a decision rule-based algorithm for reproducible risk of bias assessment of seroprevalence studies.
Bobrovitz N, Noël K, Li Z, Cao C, Deveaux G et al. (2023), Research synthesis methods
Research Interests
Research in the Computational Health Information (CHI) Laboratory focuses on the development of real in-hospital and in-home systems for AI-driven interventions that are used in practice. Translation into low- and middle-income countries (LMICs) is a parallel research theme. The lab has a focus on non-imaging AI methods: time-series analysis, -omics data, and sensor informatics.
Please see our lab research page for details.
Most Recent Publications
IMAE for noise-robust learning: mean absolute error does not treat examples equally and gradient magnitude’s variance matters
Wang X, Hua Y, Kodirov E, Clifton D & Robertson NM (2023)
An adversarial training framework for mitigating algorithmic biases in clinical machine learning.
Yang J, Soltan AAS, Eyre DW, Yang Y & Clifton DA (2023), NPJ Digit Med, 6(1), 55
Heterogeneity in diagnosis and prognosis of ischaemic stroke subtypes: 9-year follow-up of 22000 cases in Chinese adults.
Chun M, Qin H, Turnbull I, Sansome S, Gilbert S et al. (2023), Int J Stroke, 17474930231162265
On the Effectiveness of Compact Biomedical Transformers.
Rohanian O, Nouriborji M, Kouchaki S & Clifton DA (2023), Bioinformatics
SeroTracker-RoB: a decision rule-based algorithm for reproducible risk of bias assessment of seroprevalence studies.
Bobrovitz N, Noël K, Li Z, Cao C, Deveaux G et al. (2023), Research synthesis methods
DPhil Opportunities
CHI Lab offers a wide range of complex, real-world projects in AI for healthcare. Please contact Professor Clifton for enquiries.
Most Recent Publications
IMAE for noise-robust learning: mean absolute error does not treat examples equally and gradient magnitude’s variance matters
Wang X, Hua Y, Kodirov E, Clifton D & Robertson NM (2023)
An adversarial training framework for mitigating algorithmic biases in clinical machine learning.
Yang J, Soltan AAS, Eyre DW, Yang Y & Clifton DA (2023), NPJ Digit Med, 6(1), 55
Heterogeneity in diagnosis and prognosis of ischaemic stroke subtypes: 9-year follow-up of 22000 cases in Chinese adults.
Chun M, Qin H, Turnbull I, Sansome S, Gilbert S et al. (2023), Int J Stroke, 17474930231162265
On the Effectiveness of Compact Biomedical Transformers.
Rohanian O, Nouriborji M, Kouchaki S & Clifton DA (2023), Bioinformatics
SeroTracker-RoB: a decision rule-based algorithm for reproducible risk of bias assessment of seroprevalence studies.
Bobrovitz N, Noël K, Li Z, Cao C, Deveaux G et al. (2023), Research synthesis methods
