I am a statistical developer with the Delphi research group, which provides realtime and historically versioned epidemic data and forecasts, with the eventual goal to make epidemic forecasting as reliable as weather forecasts. Before this I did an Applied Math PhD at UC Davis, working with professor Naoki Saito. My undergraduate was at UW Madison, where I studied mathematics, computer science, and physics. I grew up in the idyllic Rochester, Minnesota. My broad research interests at the moment are

• Interpretable Machine Learning
• Harmonic Analysis
• Timeseries forecasting

My PhD dissertation was on understanding how to interpret classification of sonar signals using the scattering transform, both through theoretical analysis of the physical problem, and signal domain recreation of the used coefficients, in a similar manner to the circuits work for convolutional neural networks, as well as some experimentation in Generalized Scattering Transforms using Shearlets. I also implemented a continuous wavelets package and a Scattering Transform package in Julia to enable all that.

Less formally, I try to think about how we can use our roughly 80k workhours for good¹, play board/video/tabletop games, attempt to read broadly, and generally eat the internet.