Socially assistive robotic (SAR) systems apply algorithms for social human-robot interaction in order to help people achieve their goals in health-and-wellness and education settings. Research in the Interaction Lab at USC focuses on developing algorithms and approaches that enable robots to serve as hands-off helpers, provide coaching, motivation, and social skills therapy, and engage in other goal-directed social interactions with users. This talk will provide an overview of recent work from the Interaction Lab, including exploring the role of self-efficacty in post-stroke rehabilitation, understanding the role of animacy in child-robot interactions with children with autism, developing systems for long-term child-robot interaction, and modeling the role of moderator for multi-party SAR.
Elaine Short is a sixth year PhD candidate (expected graduation, May 2017) at the University of Southern California, and the recipient of a NSF Graduate Research Fellowship and a USC Provost's Fellowship. Since her time as an undergraduate at Yale University (where she graduated with a B.S. in Computer Science), she has been involved in research in human-robot interaction and socially assistive robotics, including work with children and the development of algorithms that enable robots to influence the progression of human-robot interactions. Her current research focuses on defining and modeling the role of moderator, an individual that enables a group to achieve some task in an optimal way. Such a moderator will then be used to improve group learning with children, especially in groups including one or more children with developmental or learning challenges.