David Feil-Seifer

 

Dave’s research interests include socially assistive robotics (SAR), particularly the study of Human-Robot Interaction (HRI) for children with autism spectrum disorders (ASD). He was awarded a National Science Foundation Computing Innovation Fellowship to support his work. The focus of Dave’s research is to use probabilistic models of social behavior and develop methodologies for applying these models as part of autonomous robot systems. The understanding gained from the study of social behavior is necessary for enabling technology for the increasingly complex interaction scenarios which characterize the embodied and social world.

 

 

Dave received his M.S. in Computer Science in 2007 and Ph.D. in Computer Science in 2011 from the Viterbi School of Engineering (VSoE) at the University of Southern California. He worked in the Interaction Lab advised by Prof. Maja Matarić. His dissertation research presented a data-driven methodology and a validated experimental framework for enabling fully autonomous robots to interact with typically developing children, neurotypical adults, and children with ASD in undirected scenarios using socially appropriate behavior, especially where spatial interaction is concerned. This work utilized data-driven models of social behavior in order to enable autonomous robots to recognize and appropriately respond to a child’s free-form behavior in unstructured play contexts. The focus on free-form behavior was inspired by and grounded in existing approaches to therapeutic intervention with children with ASD.