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After completing my BSc in Mathematics here at Wilfrid Laurier University, I moved to Western University for my MSc and PhD in Statistics. In these studies, I primarily focused on spatial point process modelling with applications to locations of forest fires as well as shot locations in professional hockey games.
My postdoctoral research was also at Western, but in the department of Pathology and Laboratory Medicine. I started soon after the global pandemic, and thus my research pivoted to COVID-19 research. I developed models for detecting new genetic variants using genetic sequence data sampled from wastewater. At this position, I also lead a boot camp on machine learning methods, which allowed me to further my expertise in data science.
In my current position, I am building on these models for sequence data from wastewater by extending them through time and space. My hockey analysis used unsupervised learning methods that I can also apply to wastewater sequences!
Proportions of variants of concern are estimated based on the observed mutations in the wastewater samples. These are very noisy, and I'm currently developing models that smooth this noise over space and time.
Variants of the virus that causes COVID-19 are not easily defined by a list of mutations, so I'm attempting to develop unsupervised methods to estimate proportions without first needing to know the exact mutations that determine a variant.
I also recognize the value of breadth and seek opportunities to learn new methods, so I am continuing work on models for sports analytics that may find value in other fields (and vice versa).
I have research opportunities for undergraduate and master's students with interest in modelling the pandemic, modelling ecological processes, evaluating properties of mathematical models, and sports analytics.
- DATA200: Data Anlytics
- ST494: Statistical Learning