I am a research scientist at Google working on efficient training methods for machine learning, especially for large-scale models. I received a Ph.D. in applied mathematics from the University of Wisconsin-Madison, and did a postdoc with Dimitris Papailiopoulos.

I am an erstwhile mathematician. My first paper in graduate school developed algorithms for efficiently generating random factored ideals in number fields. If this means anything to you, please reach out. Thinking in this way eventually led me to machine learning and optimization, and so here I am. In my spare time, I foster animals, bake, and participate in a Flyball team.