Originally trained as an evolutionary biologist, my research traverses various fields including phylogenetic modelling, comparative analysis, biogeography, epidemiology (phylodynamics), and most recently machine learning in public health. My past work has largely focused on explaining how and why molecules evolve (these molecules being the genes of animals or pathogens), using a broad diversity of statistical approaches. In collaboration with multiple genome-sequencing consortia, my work connects processes at the 'macro' scale (macroevolution, macroecology, phylogeography) with those at the 'micro' scale (molecular evolution). One broad question being: how and why does novel living beings and pathogens emerge?

I am now embarking on the exciting challenge of identifying infection in livestock and wildlife using techniques from computer vision. The link between animal movement (neuroscience), infection (epidemiology), and genomics is an exciting budding field that will requre a truly interdisciplinary team.