I am a clinical assistant professor with the College of Natural Sciences at the University of Texas at Austin and a postdoctoral fellow affiliated with the Building-Wide Intelligence Project and the Learning Agents Research Group under the co-supervision of professors Raymond Mooney and Peter Stone in the Department of Computer Science. Currently I am working on grounded language learning for autonomous agents operating in work environments. Previously, I was a postdoctoral fellow at the CARIS Lab at the University of British Columbia where I war advised by Professor Elizabeth Croft. There, I worked on CHARM (Collaborative Human-Focused Assistive Robotics for Manufacturing). The goal of collaborative manufacturing is to break down the barriers in factories that separate robots from humans, allowing them to safely work alongside one another. Similar to my work at UT Austin, my role was to develop mechanisms to allow humans and robots to clearly, naturally communicate with one another, enabling them to quickly, safely, and effectively work together. In September 2014, I defended my dissertation at Yale University where I researched in the Social Robotics Lab, advised by Professor Brian Scassellati. For my PhD research, I constructed a robot that is able to autonomously learn about its sensory and motor capabilities, breaking from the standard practice in which such models, if present at all, are constructed during the design of the robot, by engineers, or meticulously calibrated offline. If robots are able to understand themselves in this way, it will open the possibility of highly robust machines that are able to adapt flexibly to different use cases or to damage, in software, and very precise machines that continuously self-calibrate. The models that my robot constructs are inspired by the process by which children learn about their sensory and physical capabilities and how they are able to interact with the environment, which represent the earliest forms of self-awareness to develop during infancy.