Brett Ponsler

Worcester Polytechnic Institute, iRobot (United States)

Papers

Total Citations

299

H-Index

About

Brett Ponsler is a researcher whose work sits at the intersection of human-robot interaction, cognitive modeling, and social robotics. His primary contributions lie in developing computational models that enable robots to recognize and generate the subtle, non-verbal cues—such as directed gaze, mutual facial gaze, adjacency pairs, and backchannels—that underpin human engagement. His most influential paper, “Recognizing engagement in human-robot interaction” (2010), has garnered 251 citations and established a foundational framework for how humanoid robots can perceive and respond to social signals in real time. Building on this, Ponsler created a reusable ROS module for generating connection events during human-robot collaboration (2011, 41 citations), a practical tool that has advanced the field’s ability to design more natural, responsive robotic partners. His work on hand-eye coordination in humanoid robots (2009) further demonstrates his interest in integrating perception and action. By formalizing the mechanics of social engagement, Ponsler has helped bridge the gap between human communicative behavior and robotic implementation, making his research essential reading for anyone interested in building robots that can truly collaborate with people.