Eric completed his senior thesis at Swarthmore on walking pattern generation for humanoid robots. Prior to obtaining his Masters in Computer Science at UW-Madison, Eric worked as a developer in field of healthcare software. He is currently pursuing a PhD in Robotics at Georgia Tech, with a focus in reinforcement learning and learning from demonstration, and an overarching goal of enabling robots for discretionary use. He believes that the next step forward in artificial intelligence is to broaden access of tangible benefits from robot learning to individuals. A key challenge lies in accessibility, with the threshold still set high for non-experts to interact with and leverage robots in a meaningful manner. As advancements in robotics carry artificial intelligence from virtual environments to the physical world, it becomes critical that human robot interaction becomes both intuitive and adaptable. His current research is aimed at learning robust, interpretable, robot plans and situational context from human demonstrations.