StatML CDT student
I am a second year DPhil student studying on the Modern Statistics and Statistical Machine Learning CDT. Following the completion of my undergraduate studies in my home-city of Christchurch, New Zealand, my research career was born within the COVID-19 pandemic. Between March 2020 and September 2021 I worked in a government-funded modelling programme, applying mathematical and statistical methods to directly inform New Zealand’s COVID-19 policy. It was this experience – using statistical methods in real time to inform policy – that lead me to pursue a DPhil. I have an undergraduate degree in Statistics and Financial Engineering from the University of Canterbury (2018), and a first-class honour’s degree in Applied Mathematics (2019) from the same university. In addition to being enrolled at University College, Oxford, I am also an affiliate student at Imperial College London.
Broadly speaking, my interests are in the statistical and mathematical modelling of infectious diseases. More specifically, I am interested in:
- Methodological improvements that allow us to make improved inferences about the state of infectious disease outbreaks
- The modelling-policy interface
- Real-time outbreak analysis, particularly of novel or recently imported infectious disease, and low-incidence scenarios