Papers

13

Total Citations

516

H-Index

10

About

Bernd Kiefer is a leading researcher in human-robot interaction, specializing in the design of social robots capable of forming long-term, adaptive relationships with humans—particularly children. His work is central to the ALIZ-E project, where he pioneered methods for multimodal child-robot interaction that enable robots to build genuine social bonds through coordinated, context-aware behavior. Kiefer’s major contributions include developing multi-activity switching strategies to sustain young users’ engagement over time, as demonstrated in his 2015 paper (101 citations), and advancing socio-cognitive engineering (SCE) methodologies for robotic partners that support children’s diabetes self-management (51 citations). His research on cloud-based robot systems (22 citations) and hybrid teams combining humans, robots, and virtual agents (28 citations) has pushed the boundaries of flexible, real-world collaboration. With over 500 total citations, Kiefer’s work has been instrumental in moving social robots from lab prototypes to practical, long-term applications in healthcare and education. His 2013 paper on multimodal interaction (206 citations) remains a foundational reference for designing robots that elicit trust and disclosure from young users, cementing his reputation as a pioneer in child-robot interaction.

Research Focus

Key Achievements

10
H-Index
13
Papers
516
Total Citations
40
Avg Citations/Paper
🏆 Most Cited Paper
Multimodal Child-Robot Interaction: Building Social Bonds
206 citations · 2013
📈 Most Prolific Year: 2016 (3 Papers)
🤝 Key Collaborators: 73
🏛 Institutions: German Research Centre for Artificial Intelligence

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago