Stephan Vonschallen

ZHAW Zurich University of Applied Sciences

Papers

1

Total Citations

2

H-Index

1

About

Stephan Vonschallen is a pioneering researcher at the intersection of human-robot interaction, gerontechnology, and persuasive design. His work focuses on developing socially assistive robots that can meaningfully engage with elderly populations, particularly through generative AI and knowledge-based systems. Vonschallen’s most cited paper, "Knowledge-Based Design Requirements for Persuasive Generative Social Robots in Eldercare" (2025), establishes a foundational framework for creating robots that are not only functional but also persuasive—capable of encouraging healthy behaviors, social interaction, and independence among older adults. This work has already garnered early attention (2 citations), signaling its growing influence in a rapidly expanding field. His contributions are notable for bridging theoretical design principles with practical, ethical considerations for vulnerable users. By integrating generative AI into social robotics, Vonschallen is helping to shape the next generation of empathetic, adaptive care technologies. His research holds significant promise for addressing global challenges in aging populations, making him a key voice in the future of eldercare robotics.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
Knowledge-Based Design Requirements for Persuasive Generative Social Robots in Eldercare
2 citations · 2025
📈 Most Prolific Year: 2025 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: ZHAW Zurich University of Applied Sciences

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago