About my research interests
My area of research is broadly at the interface between statistics and life sciences where I am interested in developing scientific models alongside Bayesian statistical methodologies that allow us to infer these from (increasingly large) spatio-temporal and/or longitudinal time series data. The modeling often involves very interesting non-linearities and stochastic processes that give rise to novel statistical methodologies that are computationally challenging. I am in particular interested in the modelling of oscillatory phenomena in biology (epidemics, gene expression, molecular clocks, etc) combined with the analysis of temporal and/or spatio-temporal data (from single cells to meta-populations) and have worked on applications in epidemiology (dynamics of infectious diseases), analytical population dynamics in ecology, transcriptional dynamics of genes and large actigraph data sets obtained from wearable devices.
My collaborations also include addressing statistical and mathematical questions in chronobiology and circadian rhythm with collaborators in the biological sciences and medicine. In a project funded by the Medical Research Council (MRC) I am collaborating with members of the Chronotherapy group at Warwick and INSERM France, to develop statistical methods and models for large data sets of biomarkers on circadian oscillations, including actigraphic data from wearable devices, with the aim of using these for personalized medicine and treatment of cancer patients in their home, and basic research in chronobiology.
Current and recent PhD students:
Silvia Calderazzo, Simone Tiberi, Panayiota Touloupou (with S Spencer), Elena Camacho-Aguilar (with D Rand), Mans Unosson (with A Johanson), Beniamino Hadj-Amar (Oxford-Warwick Statistical Programme DTC), Sida Chen (Statistics), Yiyuan Zhang (with J Brettschneider).
Postdoctoral Collaborators on Research Grants:
Qi Huang, Giorgos Minas, Hiroshi Momiji.
Collaboration with groups in Mathematics, Life Sciences and Medicine led by:
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Telephone: 024 7657 2580