My research interests lie in the intersection of robotics, computer vision, and machine learning. My long term goal is to enable robots to operate in complex and diverse environments designed for humans. To achieve this goal, robots need to both be able to act based on their perception of the environment and take actions in order to improve their perception of the environment. The focus of my research is how to actively choose data to train convolutional neural networks online which I think is key to enabling successful robot autonomy in a varied and changing world.
Prior to starting my PhD, I was a Senior Software Engineer at Lockheed Martin Corporation where I worked from 2014 to 2019. I received an M.A. in Mathematics, M.A. in Economics, and B.S. in Mathematics and Economics from The University of Alabama in 2014.
RoboNet: Large-Scale Multi-Robot Learning.
Conference on Robot Learning (CoRL), 2019.
NeurIPS Workshop on Deep Reinforcement Learning, 2019.