About

Manuel Giuliani is a prominent researcher in human-robot interaction (HRI), whose work spans social robotics, robot error handling, and industrial applications of robotic systems. His most influential contribution, "To Err Is Robot" (2017, 236 citations), pioneered the study of how humans perceive and respond to faulty robot behavior, fundamentally shaping our understanding of trust and error recovery in HRI. Giuliani has made significant strides in developing socially intelligent robotic systems, notably through his robot bartender research, which demonstrated how robots can manage complex, multi-party interactions in dynamic public environments. His work on gaze control systems and user engagement classification has advanced the field of socially aware robotics, enabling machines to interpret and respond to subtle human social signals. Beyond social robotics, Giuliani has contributed to industrial HRI through activity recognition systems and augmented reality tools for robot programming, as well as comparative analyses of robot simulation platforms. More recently, his exploration of swarm robotics and mutual shaping highlights his commitment to understanding real-world deployment challenges. With over 900 citations across his top works, Giuliani's research continues to bridge the gap between technically capable robots and genuinely human-centered interaction.

Research Focus

Key Achievements

23
H-Index
68
Papers
1,833
Total Citations
27
Avg Citations/Paper
🏆 Most Cited Paper
To Err Is Robot: How Humans Assess and Act toward an Erroneous Social Robot
236 citations · 2017
📈 Most Prolific Year: 2013 (7 Papers)
🤝 Key Collaborators: 187
🏛 Institutions: University of the West of England, Fortiss, University of Salzburg, Bristol Robotics Laboratory, Technical University of Munich, Embedded Systems (United States)

Top Papers

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    Two people walk into a bar
    92 citations · 2012
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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 34 days ago