About

Hi, I'm Taylor and I'm a statistics nerd.

Once upon a time I dreamed of being an economist; I had read Freakonomics and fallen in love with exploring the hidden side of everything. Fortunately I stumbled into a statistics class at Duke and never looked back.

After my indoctrination into Bayesian statistics I broadened my perspectives at Carnegie Mellon. My PhD work adapated standard ML algorithms such nearest neighors, random forests, and neural networks to perform conditional density estimation with applications in multimodal uncertainty quantification and Approximate Bayesian Computation. Academia was nice but it was impossible to withstand the allure of indu$try.

I started my career in experiment design and analysis for Google search ads. These days I'm at YouTube, thinking about generative AI.

When I'm not working or writing I'm likely outside competing in orienteering and adventure races. The heart of these sports shares the same core as my work life: navigating uncertainty to make better decisions. Just with cardio and sleep deprivation.

This blog is a space for me to think out loud. The technical posts are the main event: side projects, techniques I've found useful, and observations worth writing up with some care. The ephemera section sits lower to the ground. These are quicker reflections on talks I attend, books I read, plays I watch, and puzzles I pick at. I write those mostly to work things out for myself, but I try to leave behind the note I wish I'd found; if you're chasing the same thread, it might save you some time.