I analyse signatures left by population dynamic processes and selective pressures in pathogen genomes. These signatures contain important information about the spread and adaptation of infectious diseases. In particular, I am interested in the potential of phylodynamic methods to produce rapid and accurate inferences of key epidemiological parameters and inform public health policy during emerging and re-emerging infectious disease outbreaks. I further aim to identify scenarios where current methods fail when confronted with the biases inherent in real-world data and develop new methods that are robust to such biases. I am also interested in developing methods for total-evidence epidemiological inferences, combining different types of data (such as genomic and surveillance data) in an integrated framework. Finally, I am interested in finding ways to better visualise and communicate results to both scientists and non-scientists alike.