I am a lecturer at the School of Computing at the University of Otago in Dunedin, New Zealand.

My research interests are in mathematical and computational phylogenetics and their intersection with machine learning. I’m interested in how we can make tree search and inference more efficient for large-scale datasets, e.g. to study virus evolution. Machine learning holds real promise here, but to be trusted as part of phylogenetic pipelines, models need to be more than accurate black boxes. By carefully designing machine learning models based on the structure of phylogenetic data and evolutionary processes, I aim to understand what these models actually learn, with the goal of making these black-box predictions more interpretable. My broader goal is to build methods that are not just accurate, but understandable enough to be trusted for phylogenetic inference at scale.