Jiaqi Gong

University of Alabama, University of Virginia

Papers

5

Total Citations

51

H-Index

4

About

Jiaqi Gong is a leading researcher at the intersection of human-robot collaboration, intelligent healthcare systems, and adaptive manufacturing. His work focuses on enhancing human-robot teaming by integrating physiological sensing, reinforcement learning, and real-time communication to optimize performance and safety. Gong’s major contributions include developing a Q-learning-based framework that dynamically adjusts task loads using physiological data, significantly improving team efficiency in Industry 4.0 and 5.0 environments. His highly cited review on purposeful communication in human-robot collaboration (25 citations) provides a comprehensive analysis of modern manufacturing approaches, addressing critical challenges in shared understanding. He also pioneered a robot-assisted emergency system for elderly independent living (11 citations), combining tele-controlled co-robots with voice and video communication to enhance safety for aging populations. Additionally, Gong’s work on motion marker discovery from inertial sensors (4 citations) advances objective assessment of robotic surgical skills, while his eye movement analysis framework (2 citations) predicts teaming performance under varying task loads. His research has profound implications for manufacturing, healthcare, and assistive robotics, demonstrating a commitment to creating adaptive, human-centered autonomous systems.

Research Focus

Key Achievements

4
H-Index
5
Papers
51
Total Citations
10
Avg Citations/Paper
🏆 Most Cited Paper
Purposeful Communication in Human–Robot Collaboration: A Review of Modern Approaches in Manufacturing
25 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: University of Alabama, University of Virginia

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago