Parag Khanna

KTH Royal Institute of Technology

Papers

8

Total Citations

43

H-Index

4

About

Parag Khanna is a robotics researcher specializing in human-robot interaction, collaborative robotics, and robot failure communication. His work sits at a compelling intersection of robot design, social intelligence, and human-centered computing, with a particular focus on making robots more intuitive and trustworthy partners in collaborative tasks. Khanna's most influential contribution lies in understanding how robots should communicate failures to human collaborators. His 2023 paper on explanation strategies for resolving robot failures has garnered 13 citations, establishing foundational insights into how robots can maintain user trust and task efficiency even when things go wrong. This work has since evolved into the REFLEX dataset project — a multimodal resource capturing human reactions to robotic failures and explanations — demonstrating his commitment to building open research infrastructure for the community. Beyond failure communication, Khanna has made notable contributions to the mechanics of human-robot handovers, publishing experimental studies on grip-release dynamics and multimodal handover datasets that inform how robots can achieve more natural, fluent physical interactions with people. His earlier work on low-cost underactuated prosthetic hands reflects a longstanding interest in accessible, biomimetic robotic design. Collectively, his research advances a vision of robots that collaborate gracefully, recover intelligently, and adapt meaningfully to human behavior.

Research Focus

Key Achievements

4
H-Index
8
Papers
43
Total Citations
5
Avg Citations/Paper
🏆 Most Cited Paper
Effects of Explanation Strategies to Resolve Failures in Human-Robot Collaboration
13 citations · 2023
📈 Most Prolific Year: 2023 (3 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: KTH Royal Institute of Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago