As a mathematical biologist I am interested in mathematics as a tool to study biological systems. These systems are often complex and multiscale. The objective is to abstract the key components and mechanisms of the system into a mathematical model. Analysis of this model can provide insights into how the system functions, lead to recommendations for system control or management and generate predictions for system behaviour. The development and analysis of these mathematical models may involve theory and techniques from diverse areas of mathematics including dynamical systems, partial differential equations, numerical methods, stochastic processes, computational simulation, machine learning and statistics.

A wide range of biological systems interest me. However, the majority of my research is concerned with the epidemiology and evolution of infectious diseases. My work aims to address questions related to how seasonal variability, spatial heterogeneity and social structure influence a population’s vulnerability to epidemics, the way epidemics unfold, and how they may be controlled. I am also interested in the interaction between epidemiological dynamics and microbial evolution. These processes occur on similar timescales and their entanglement underscores the importance of accounting for evolution in strategies to manage infectious diseases.