Chris works at the interface between epidemiology, infectious disease modelling, statistics, and high performance computing. He originally trained as a veterinary surgeon, but became interested in epidemics through his experience working on the foot and mouth disease outbreak in the UK in 2001. He believes strongly in application-focused statistical research and in effective communication of scientific outputs. Chris' interests lie in decision support systems for disease outbreak response, public health and zoonotic diseases. He has applications in communicable diseases such as foot and mouth disease, influenza and COVID-19, vector-borne diseases such as theileriosis, and anti-microbial resistance. In computational statistics, he works on MCMC methods for inference on stochastic dynamical models. He has a particular interest in high performance computing techniques for applying modern statistical methods to real-time inference on large population datasets.