Samuel Fernando

University of Sheffield

Papers

17

Total Citations

281

H-Index

10

About

Samuel Fernando is a researcher specializing in human-robot interaction (HRI), with a particular focus on social robotics, child-robot interaction, and the role of emotional expression in shaping human perceptions of robotic systems. His work has made significant contributions to understanding how children engage with humanoid robots, exploring questions of animacy, trust, and emotional responsiveness in real-world educational settings. Fernando's most cited work, "The Effects of Robot Facial Emotional Expressions and Gender on Child-Robot Interaction" (2018, 39 citations), investigates how lifelike affective expressions in the humanoid robot Zeno influence children's behavior and attitudes. Complementing this, his 2015 paper on trust in HRI (35 citations) provides a valuable interdisciplinary framework for understanding the contextual and individual factors that shape human-robot trust. His involvement in the EU-funded EASEL Project further reflects his commitment to developing symbiotic educational robots capable of meaningful tutoring interactions. Across his body of work, Fernando consistently highlights how age, perception of animacy, and emotional design affect children's acceptance of robotic companions. With over 240 cumulative citations, his research offers important insights for designers and educators seeking to deploy socially intelligent robots in learning environments effectively.

Research Focus

Key Achievements

10
H-Index
17
Papers
281
Total Citations
17
Avg Citations/Paper
🏆 Most Cited Paper
The effects of robot facial emotional expressions and gender on child–robot interaction in a field study
39 citations · 2018
📈 Most Prolific Year: 2015 (6 Papers)
🤝 Key Collaborators: 36
🏛 Institutions: University of Sheffield

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago