Since first using statistics to uncover trends in medieval music, I have committed myself to finding novel and creative ways to use data. My research includes Scrabble analysis and pizzeria proximity — there's rarely a topic I find too trivial for rigorous study.
With a passion for public service, I have also built many tools to provide government oversight and visualize complicated issues. I am optimistic about the possibilities of applied mathematics, particularly machine learning, to inform debate and serve the public good. I currently work full-time building machine learning models that increase efficiency on the electrical grid.
At university, I studied music and physics, and I have worked as a software engineer, data scientist, and journalist.