About

I am a computer scientist and computational/mathematical modeller and currently a Research Fellow (Core Scientist) at The Roslin Institute (University of Edinburgh). Over my career, my research has focussed on the computational modelling of systems to help improve the understanding of the natural and synthetic world.

My current research focuses on developing veterinary epidemiological models for UK agricultural disease. This includes computational modelling of disease transmission based on real-world scenarios, as well the analysis for understanding the associated risk factors and the mitigation of disease spread.

I am working on machine learning models for improving disease diagnostics, incorporating epidemiological and environmental risk factors into the interpretation of diagnostics tests. This has been applied to bTB skin testing and I am working on further applications. I also work on combining land use statistics, economic models of land use change, and species distributions to estimate infectious disease risks due to land use and climate change.

Prior research on COVID-19 contributed to the response to the pandemic and advising Public Health Scotland and Scottish Government. I also assist with the management of our group, its data, models, and outputs.

Current specific topics of interest include: machine learning models for exploring large parameter spaces with environmental, phylogenetic, and risk factor features; machine learning models for improving diagnostic testing; deep learning image classification from CT images and microscopy for disease diagnostics and developmental research; detailed individual-based models using distributed / cloud computation; inference of model parameters with Bayesian techniques (e.g. ABC).