People
Academic Staff
Listed below are some of the members of Statistics who are interested in or actively working on topics in medicine or molecular biology. Also given are some of the areas of interest relevant to this group, although these are necessarily incomplete.
Dr Benjamin Baer – causal inference, interpretable hypothesis testing, survival analysis
Professor Rosemary Bailey – Design of experiments, Clinical and pre-clinical trials, Forensic statistical analyses of controversial medical studies
Dr. Christina Fell – Deep learning for medical images, automated cancer detection, neuroimaging classification.
Professor Andy Lynch – Methods for high-throughput genomics technologies, Cancer research (esp. prostate cancer), Statistical Genomics
Dr Nicolo Margaritella – Bayesian statistics with applications
to neuroscientific data
Dr Giorgos Minas – Systems biology, Adaptive clinical trial design, Neuroimaging
Dr Elham Mirfarah – Application of mixture models in survival data analysis.
Dr Michail Papathomas – Methods for Genome-Wide Association Studies, Complex phenotypes/diseases, Statistical genetics
Dr Ben Swallow – Inference and modelling for cell-signalling and for infectious disease and pandemics.
Dr Hannah Worthington – Estimating population sizes. Applying ecological methods to molecular data.
Research Staff
Wei Jing – Applying Bayesian methods on the HATUA project
Research Students
Konstantinos Alexiou – Stochastic modelling of populations of interacting cells with complex underlying phenotypes
(Supervisor: Minas)
Naici Guo – Collaborating with members of the School of Medicine on analysis of proteomics data.
(Minas, Lynch)
Katie O’Neill – Linking small RNA and pathology data in prostate cancer (School of Medicine)
(Lynch, Worthington)
Victor Velasco Pardo – Developing methods for uncertainty of signatures.
(Lynch, Papathomas)
Hanyu Wang – detecting prevalent clusters of Multimorbidity with uncertainty evaluation using Bayesian Mixture Modelling and subsampling
(Margaritella, Papathomas)
Xioayue Yang – Methods evaluation and development for prostate gene expression data.
(Lynch, Minas)