I recently received my Ph.D. in Electrical and Computer Engineering from UCLA, where I was advised by Dr. Brett Lopez at the Verifiable & Control-Theoretic Robotics (VECTR) Laboratory and developed state-of-the-art 3D LiDAR SLAM algorithms for unstructured GPS-denied environments. I have spent time at Exyn Technologies, where I conducted SLAM R&D on the Autonomy and Mapping team, NASA JPL, where I led the development of localization and mapping algorithms for aerial vehicles for the DARPA Subterranean Challenge, and HRL Laboratories, where I worked on a variety of interesting computer vision problems. Prior to my Ph.D., I received a B.S. and M.S. from UC San Diego in 2017 and 2018 and conducted computer vision research at the Translational Neuroengineering Laboratory.

I am broadly interested in robotic perception, spanning fields such as computer vision, machine learning, state estimation, and numerical optimization. My long-term research objective is to enable fast and robust, human-like geometric and semantic perception capabilities for mobile robots through innovative algorithmic design grounded by first principles. Towards this, much of my work has focused on the development of general, domain-agnostic 2D/3D algorithms that are resilient to outliers and are practical and real-time.

Life goals include helping to advance our engineering capabilities in assistive and exploratory robotics, and one day seeing the Clippers win an NBA championship.