Amol Deshmukh
Papers
33
Total Citations
331
H-Index
12
About
Amol Deshmukh is a researcher whose work sits at the intersection of human-robot interaction, social robotics, and affective computing. His scholarship focuses on how robots and virtual agents can communicate more naturally and effectively with humans — exploring embodiment preferences, gesture design, personality attribution, and empathic tutoring systems. Among his most influential contributions is a body of work examining how robotic gesture parameters — such as amplitude and speed — shape users' perceptions of robot personality and social qualities, as measured by the widely-used Godspeed questionnaire. This line of research, accumulating over 60 combined citations, offers practical design guidelines for engineers and researchers building socially expressive robots. His investigations into the attraction paradigm in human-robot interaction further challenge assumptions about personality matching and likability. Deshmukh has also made meaningful contributions to educational robotics, developing empathic virtual tutors with memory capabilities for children's learning environments, and has extended his work into real-world public deployments through the EU-funded MuMMER project. Perhaps most notably, his study on using social robots to promote hand-washing among schoolchildren in rural India demonstrates a commitment to applying HRI research toward tangible social good, showcasing both the breadth and humanitarian ambition of his research agenda.
Research Focus
Key Achievements
Top Papers
- 1How Do You Like Me in This: User Embodiment Preferences for Companion Agents24 citations · 2012
- 2Shaping Robot Gestures to Shape Users' Perception23 citations · 2018
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- 6Evaluating a social multi-user interaction model using a Nao robot19 citations · 2014
- 7MuMMER: Socially Intelligent Human-Robot Interaction in Public Spaces17 citations · 2019
- 8I'm the mayor: a robot tutor in enercities-216 citations · 2014
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