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About

Aaron Holroyd is a robotics and human-computer interaction researcher whose work has significantly advanced the understanding of how humans and robots engage with one another in natural, collaborative settings. His primary research focus lies in **human-robot interaction (HRI)**, with particular emphasis on modeling and generating engagement behaviors that allow robots to interact more intuitively with people. Holroyd's most influential contribution is his computational model for recognizing engagement in human-robot interaction, introduced in a 2010 paper that has accumulated over 349 citations across multiple venues — a testament to its foundational impact on the field. This model identifies four key "connection events" — directed gaze, mutual facial gaze, adjacency pairs, and backchannels — drawn from studies of human-to-human engagement and applied to humanoid robotics. Building on this work, his 2011 research on generating connection events demonstrated how these principles could be practically implemented as a reusable Robot Operating System (ROS) module, earning 41 additional citations. His later contributions explored Behavior Markup Language (BML) realizers tailored for robotic — rather than virtual agent — applications, and early work in hand-eye coordination for humanoid robots. Holroyd's research has helped lay the groundwork for socially aware robots capable of meaningful, responsive interaction with humans.