Emily Somerset

PhD Candidate, Department of Statistical Sciences, University of Toronto

Emily Somerset

Projects:

spatiotemporal models to predict COVID-19 prevalence in wastewater

I’m a 2021 cohort PhD candidate at the University of Toronto, supervised by Patrick Brown and Monica Alexander. I am interested in statistical methods for demography and epidemiology. More specifically, I am currently working on problems involving spatiotemporal models to predict COVID-19 prevalence in wastewater, large matrices for national migration, and causes of health outcomes estimation from verbal autopsy data and in censored data contexts.

Before starting my PhD, I worked as a biostatistician for 3 years at the University Health Network and Hospital for Sick Children. I received my bachelor’s degree in Applied Mathematics (minor in statistics) from Waterloo University and my MSc degree at Queen’s University. For my MSc thesis, I developed 3 statistical tests for periodic correlation in time series data, applied it to the interplanetary magnetic field data and uncovered evidence for periodic behavior in its autocorrelation function.