About

Hey! Thanks for coming to my website.

I’m a computational scientist with broad interests in developing tools and methods to support scientific inquiry. This includes developing domain-informed machine learning (ML) algorithms and interpretability methods, and building systems to integrate machine learning, simulation, and experiment. I am doing my best to contribute to the vision of autonomous, AI-driven scientific discovery. (You can find a good sketch of what that really means is in this paper by a few leaders in the field).

As of September 2022, I am working towards a Ph.D. in Computer Science from the University of Chicago. Before that, worked at Los Alamos National Laboratory. The rest of the story is in my cv.

I am supported by the US Department of Energy’s Computational Science Graduate Fellowship (CSGF). You can learn more about that here (general info, my official profile).

In a former life I wanted to be a psychologist and a philosopher. This still comes out in the way I approach things, and I plan on dabbling in computational social science.

In my free time, I like going outside (hiking, gravel cycling), playing the guitar, building and driving track cars, and clicking on rocks in a classic multi-user dungeon.