Professor Jim Davies
Professor of Software Engineering
- Director, Oxford EPSRC Centre for Doctoral Training in Health Data Science
- Lead Data Scientist, National Consortium for Intelligent Medical Imaging
- Governing Body Fellow, Kellogg College, University of Oxford
Jim Davies is Professor of Software Engineering and Director of the Centre for Doctoral Training (CDT) in Health Data Science. He is leading the development of data standards and infrastructure for clinical and laboratory data across a network of NIHR Biomedical Research Centres (BRCs), as part of the NIHR Health Informatics Collaborative. He is also the Lead Data Scientist for the National Consortium for Intelligent Medical Imaging, funded by Innovate UK.
His research is focussed upon the development of new model- and metadata-driven techniques for big data engineering: techniques that support the automatic generation and configuration of software, and the automatic management and processing of data, based upon precise, abstract descriptions of structure, process, and intended interpretation. This work has been informed by practical, large-scale application in clinical research, healthcare delivery, and electronic governance.
A UK nationwide study of adults admitted to hospital with diabetic ketoacidosis or hyperosmolar hyperglycaemic state and COVID-19.
Field BCT. et al, (2023), Diabetes, obesity & metabolism
Examining variation in the measurement of multimorbidity in research: a systematic review of 566 studies
Ho IS-S. et al, (2021), The Lancet Public Health
Sixty-day consequences of COVID-19 in patients discharged from hospital: an electronic health records study.
Islam N. et al, (2021), Eur J Public Health
Efficacy and safety of tenofovir disoproxil fumarate (TDF) in hepatitis B virus (HBV) monoinfection: longitudinal analysis of a UK cohort
Wang T. et al, (2020)
National Institute for Health Research Health Informatics Collaborative: development of a pipeline to collate electronic clinical data for viral hepatitis research.
Smith DA. et al, (2020), BMJ health & care informatics, 27