I am third year doctoral candidate at UCSD in Intelligent Systems Robotics and Control (ISRC, Electrical and Computer Engineering Department). I am advised by Yuanyuan Shi with mentorship from Miroslav Krstic. Furthermore, I have been grateful to be fully supported throughout my Ph.D. by the Department of Energy Computational Science Graduate Fellowship (DOE CSGF), which has provided both resources and a community that have enriched my academic development.

Throughout my Ph.D., I have been developing deep-learning methods (neural operators) for control of dynamical systems achieving numerical speedups on the magnitude of 1000x while providing certifiable theoretical guarantees. This work has enabled me to contribute to a diverse range of applications, from controlling chemical reactions and compensating for delays in robotic manipulators to enabling discretization-invariant motion planning. For a deeper introduction to my research, please check out my most recent seminar talk on YouTube or checkout Miroslav's presentation of our work .

I did my undergrad at Vanderbilt University studying physics, applied math, and computer science. I was fortunate to be a member of the accelerated bachelors/masters program in which I was advised by Kalman Varga and Gautam Biswas.