About me

I’m an applied mathematician interested broadly in collective behavior, especially as modeled by dynamical systems on networks. My current interest is in developing methods to infer low-dimensional equations of motion directly from data.

I earned my PhD in June 2019 from UC Davis, advised by Raissa D’Souza. You can read my dissertation here.

As of September 2019 I am a postdoc in Nathan Kutz and Steve Brunton’s groups at the University of Washington. From September to December 2019, I was in residence at IPAM for their long program on Machine Learning for Physics and the Physics of Learning.

Bio

I grew up in the suburbs of Philly, then moved to upstate New York for college at RPI. After that I moved to sunny Davis, California for grad school in applied math.

I spent the summers 2016-2018 as an intern in the Center for Nonlinear Studies at Los Alamos National Lab, working primarily with Anatoly Zlotnik, Andrey Lokhov, Aric Habgerg, and Andrew Sornborger.

In my free time I enjoy climbing, hiking, cooking, listening to music, and novice flameworking.