Jiong Tang

University of Connecticut

Papers

7

Total Citations

89

H-Index

4

About

Jiong Tang is a leading researcher at the intersection of robotics, computer vision, and intelligent manufacturing, whose work is driving the next generation of automated inspection and additive manufacturing systems. His primary research areas include structural health monitoring, robotic motion planning, and AI-driven surface inspection. Tang’s major contributions lie in pioneering the use of unmanned aerial vehicles (UAVs) for non-contact structural vibration measurement and condition assessment, a field where his 2023 survey has already garnered 28 citations. He has also made foundational advances in robot motion planning, developing discretized configuration space methods that enable robots to navigate dynamic environments safely and efficiently. More recently, Tang has been at the forefront of integrating generative adversarial networks (GANs) for data augmentation in automated surface inspection, addressing the critical challenge of limited training data in manufacturing quality control. His forward-looking work on intelligent cooperative robotics in additive manufacturing, published in 2024 with 25 citations, outlines a vision for collaborative robotic systems that can autonomously adapt to complex production tasks. With a growing portfolio of highly cited papers and a clear trajectory toward practical, real-world applications, Tang is shaping the future of smart manufacturing and robotic autonomy.

Research Focus

Key Achievements

4
H-Index
7
Papers
89
Total Citations
13
Avg Citations/Paper
🏆 Most Cited Paper
Unmanned aerial vehicle-based computer vision for structural vibration measurement and condition assessment: A concise survey
28 citations · 2023
📈 Most Prolific Year: 2023 (2 Papers)
🤝 Key Collaborators: 16
🏛 Institutions: University of Connecticut

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago