Chris Holmes
Professors of Biostatistics in Genomics
I have a broad interest in the theory, methods and applications of statistics and statistical modelling. My background and beliefs lie in Bayesian statistics which provides a unified framework to stochastic modelling and information processing. I am particularly interested in pattern recognition and nonlinear, nonparametric methods.
Recent publications
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The epidemiological impact of the NHS COVID-19 App.
Journal article
Wymant C. et al, (2021), Nature
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Modelling the impact of rapid tests, tracing and distancing in lower-income countries suggest optimal policies varies with rural-urban settings
Journal article
Jiang X. et al, (2021)
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Semi-Unsupervised Learning: Clustering and Classifying using Ultra-Sparse Labels
Conference paper
Willetts M. et al, (2020), Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020, 5286 - 5295
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Epidemiological changes on the Isle of Wight after the launch of the NHS Test and Trace programme: a preliminary analysis.
Journal article
Kendall M. et al, (2020), The Lancet. Digital health, 2, e658 - e666
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Machine learning analysis plans for randomised controlled trials: detecting treatment effect heterogeneity with strict control of type I error
Journal article
Watson JA. and Holmes CC., (2020), Trials, 21