I am a recent doctoral graduate from the Modern Statistics and Statistical Machine Learning CDT at the University of Oxford, supervised by Professor Christl Donnelly and Dr Kris V Parag.
Currently, I am working as a research consultant at Verdel Instruments, where I am developing statistical and machine learning methods to analyse 2D mass spectrometry data. I am open to other opportunities in the science start-up space. Please reach out if you have an interesting problem that might benefit from my skills.
My full doctoral thesis can be found here. Key pieces of work from my thesis include:
- A decision-theoretic framework for uncertainty quantification in epidemiological models (publication/GitHub repo)
- Robust uncertainty quantification in popular epidemic models (publication/GitHub repo/vignettes)
- SMC methods for epidemic renewal models (publication/GitHub repo/website)
- Smoothing methods for epidemic survey data (publication/GitHub repo/vignettes)
- Estimating epidemiological dynamics using wastewater data (publication/GitHub repo)
- A descriptive analysis of behaviours during the COVID-19 pandemic in England (publication/data portal).
During my doctoral studies I also worked on estimating orphanhood due to COVID-19 and all-causes in Brazil and further estimation of the reproduction number (see also).
See my homepage for more information.