Papers

13

Total Citations

137

H-Index

5

About

Mayumi Mohan is a leading researcher at the intersection of human-robot interaction (HRI), assistive robotics, and rehabilitation engineering. Her work centers on designing social-physical robots that can keep older adults active and support stroke therapy, bridging the gap between human-human interaction dynamics and robot-mediated care. Her most-cited paper, “Exercising with Baxter” (68 citations), provides foundational evidence that robots can effectively motivate physical activity in aging populations. She has also made significant methodological contributions through “Lessons Learned About Designing and Conducting Studies From HRI Experts” (24 citations), helping novice researchers navigate the field’s multidisciplinary challenges. Mohan’s research uniquely quantifies human-human therapy kinematics to inform robot-patient interactions, as seen in her work on stroke rehabilitation. She has developed design tools for therapeutic HRI and explored how robots can use music, social analogues, and nonverbal feedback to enhance exercise engagement. Her achievements include leading workshops on study design and contributing to the development of the Dexto:Eka humanoid robot. With a growing citation record and a clear focus on translating human interaction principles into robotic systems, Mohan is shaping how robots can serve as effective, empathetic partners in healthcare and daily living.

Research Focus

Key Achievements

5
H-Index
13
Papers
137
Total Citations
11
Avg Citations/Paper
🏆 Most Cited Paper
Exercising with Baxter: preliminary support for assistive social-physical human-robot interaction
68 citations · 2020
📈 Most Prolific Year: 2022 (2 Papers)
🤝 Key Collaborators: 60
🏛 Institutions: Max Planck Institute for Intelligent Systems, The NorthCap University, University of Pennsylvania

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago