I’m a PhD Candidate in Systems Design Engineering at the University of Waterloo. I’ve been researching efficiency in neural networks with Alexander Wong as my supervisor.
During my PhD I’ve done a few internships, working at AWS on efficient text classification and churn prediction, and at Shell Street Labs (BFAM Partners) on volatility surface modelling. While my PhD originally was focused on medical imaging, I found that algorithmic improvement was not the bottleneck in this field, so moved to more general deep learning research.
During my Master’s in Statistics I worked on deep learning for cancerous cell detection, and presented it at SPIE medical imaging conference.
In undergrad I studied Math and Economics at Carleton University, and after graduating worked at the Bank of Canada for a year on oversight of financial market infrastructure.
PhD in Machine Learning, 2022
University of Waterloo
Master's Statistics, 2017
University of Waterloo
BMath in Math/Economics, 2015
Carleton University