Lei Clifton
Official Fellow in AI & ML, Reuben College
Statistics and AI for clinical studies
My research interest is at the interface of medical statistics and AI, with over 20 years of research experience.
I am the Programme Director of the MSc in Applied Digital Health, where I am also module leader and lecturer, working alongside the Academic Directors, Profs. John Powell and Catherine Pope.
My research focuses on a wide range of methodology, including foundation models (and large language models) for healthcare, disease prediction, and the fusion of AI with medical statistics. Much of this work collaborates closely with the "AI for Healthcare" group in the Department of Engineering Science, where I also hold an affiliation.
After studying engineering and machine learning, I did my postdoctoral training at the Department of Engineering Science (2009-14), before training as a medical statistician under Prof. Doug Altman at the Centre for Statistics in Medicine (2014-18). Subsequently, I was team leader in the Nuffield Department of Population Health (2019-24), where I led a programme of research in translational epidemiology.
When at home, I can be found painting watercolours, practising yoga, and making noise on the violin with friends.
Recent publications
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Transforming label-efficient decoding of healthcare wearables with self-supervised learning and “embedded” medical domain expertise
Journal article
Gu X. et al, (2025), Communications Engineering, 4
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A multimodal automated deep learning-based model for predicting biochemical recurrence of prostate cancer following prostatectomy from baseline MRI, Presurgical clinical covariates
Journal article
Simon BD. et al, (2025), Clinical Imaging, 126
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Beyond Correlations: The Necessity and the Challenges of Causal AI
Preprint
Chauhan VK. et al, (2025)
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Sample Selection Bias in Machine Learning for Healthcare
Journal article
Chauhan VK. et al, (2025), ACM Transactions on Computing for Healthcare
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Dysregulated immune proteins in plasma in the UK Biobank predict multiple myeloma 12 years before clinical diagnosis
Journal article
Fieggen J. et al, (2025), Blood Advances, 9, 3766 - 3770
Collaborators
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John Powell
Professor of Digital Health
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Catherine Pope
Professor of Medical Sociology
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Andrew Farmer
Professor of General Practice