About

Elizabeth Cha is a human-robot interaction researcher whose work spans nonverbal robot communication, telepresence technologies, and the integration of robots into everyday human environments. She has made foundational contributions to understanding how non-humanoid robots can effectively communicate with human collaborators, most notably through her highly cited 2018 survey on nonverbal signaling methods (98 citations), which has become an essential reference for researchers designing socially aware robots. Her investigations into perceived robot capability challenge the field's traditional focus on technical performance alone, arguing that user perception is equally critical to meaningful adoption. Cha's research on telepresence robotics has had particular impact in educational contexts, where she has explored how robots can support K-12 and university students who cannot physically attend school—work that proved especially prescient given global disruptions to in-person learning. Her studies on robot personalization, auditory localization, and social closeness further reveal how nuanced design choices shape human experience with robotic systems. With over 460 cumulative citations across her top works and research spanning laboratory, classroom, and home environments, Cha brings a distinctly human-centered lens to robotics, ensuring that technological advances translate into genuinely meaningful interactions for real users.

Research Focus

Key Achievements

13
H-Index
20
Papers
560
Total Citations
28
Avg Citations/Paper
🏆 Most Cited Paper
A Survey of Nonverbal Signaling Methods for Non-Humanoid Robots
98 citations · 2018
📈 Most Prolific Year: 2018 (4 Papers)
🤝 Key Collaborators: 34
🏛 Institutions: University of Southern California, Carnegie Mellon University, Johns Hopkins Hospital, Johns Hopkins University, École Polytechnique Fédérale de Lausanne

Top Papers

  1. 1
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    Perceived robot capability
    59 citations · 2015
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  10. 10
    Robots in the Home
    24 citations · 2015

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago