Shuoshuo Shen

Hebei University of Technology, Zhejiang Lab

Papers

6

Total Citations

125

H-Index

4

About

Shuoshuo Shen is an emerging researcher specializing in reliability engineering, robotic systems, and uncertainty quantification, with a particular focus on advancing the analytical frameworks used to evaluate the precision and dependability of industrial robots. His most celebrated contribution, "Kinematic Trajectory Accuracy Reliability Analysis for Industrial Robots Considering Intercorrelations Among Multi-Point Positioning Errors" (2022), has garnered 69 citations and introduced a sophisticated approach to modeling the complex statistical dependencies inherent in multi-point robotic positioning—a problem of critical importance in precision manufacturing environments. Building on this foundation, Shen has developed Bayesian inference-assisted frameworks for next-generation factory systems and robust optimization strategies that simultaneously address kinematic and dynamic performance criteria. His methodological innovations extend to moment estimation techniques and efficient integral approaches capable of handling both aleatory and epistemic uncertainties, making his methods broadly applicable across real-world engineering scenarios. His most recent work explores unified moment-based approaches bridging time-independent and time-dependent reliability analyses, reflecting a maturing research vision. With over 120 cumulative citations and a rapidly expanding publication record, Shen represents a promising voice in the intersection of robotics, probabilistic design, and intelligent manufacturing systems.

Research Focus

Key Achievements

4
H-Index
6
Papers
125
Total Citations
21
Avg Citations/Paper
🏆 Most Cited Paper
Kinematic trajectory accuracy reliability analysis for industrial robots considering intercorrelations among multi-point positioning errors
69 citations · 2022
📈 Most Prolific Year: 2025 (2 Papers)
🤝 Key Collaborators: 11
🏛 Institutions: Hebei University of Technology, Zhejiang Lab

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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