Papers

3

Total Citations

16

H-Index

2

About

Jingyun Zhao is a researcher at the forefront of Industry 4.0, specializing in Digital Twin (DT) technology and the interoperability of cyber-physical systems. Her work addresses a critical industrial challenge: creating seamless virtual representations of physical products and plants from heterogeneous data sources. Zhao’s most influential paper, “A Semi-Automatic Approach for Asset Administration Shell Creation from Heterogeneous Data” (2023, 10 citations), proposes a method to overcome the inconsistent interfaces between engineering disciplines, enabling the standardized digital twins essential for the value chain. She further advances the field with her architecture for a versatile Digital Twin using socket-based communication and Azure DT (2023, 4 citations), which integrates IoT, big data, and AI for real-time monitoring and optimization. Zhao’s earlier work on high-speed parallel robot dynamic modeling based on PLC (2018) demonstrates her foundational expertise in automation and control. With a growing citation impact, Zhao is a key contributor to making Industry 4.0’s vision of interoperable, intelligent manufacturing a practical reality.

Research Focus

Key Achievements

2
H-Index
3
Papers
16
Total Citations
5
Avg Citations/Paper
🏆 Most Cited Paper
A Semi-Automatic Approach for Asset Administration Shell Creation from Heterogeneous Data
10 citations · 2023
📈 Most Prolific Year: 2023 (2 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: Institute of Automation, Technical University of Munich, Henan Institute of Technology

Top Papers

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  3. 3

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago