Utilized artificial intelligence to overcome limitations of cheap hardware in a constrained quadruped robot.
Modeled a reinforcement learning problem of a constrained robot in simulation using OpenAI Gym and PyBullet.
Investigated methods for reducing the Sim2Real gap in robotic systems with limited sensing feedback.
Applied TinyML optimization techniques to reduce the size of a reinforcement learning model by 1000%.
Implemented a pipeline for deploying a Stable Baselines model on an embedded system using TFLite.
Education
Graduated from the University of Virginia in 2022 with a Bachelor's degree in Systems Engineering; currently a PhD student in Computer Science at Harvard University.
Background
A Computer Science PhD student at Harvard University, with research interests in machine learning, robotics, and autonomous vehicles. Member of the Edge Computing Lab under the mentorship of Professor Vijay Janapa Reddi.