Encheng Ma

China Academy of Building Research

Papers

1

Total Citations

3

H-Index

1

About

Encheng Ma is a pioneering researcher at the intersection of Building Information Modeling (BIM), semantic web technologies, and robotic perception. His work centers on creating intelligent, data-driven frameworks that bridge the gap between digital building models and autonomous robotic systems. Ma’s most notable contribution, "Component-based BIM-semantic web integration for enhanced robotic visual perception" (2025), introduces a novel approach that leverages semantic web ontologies to decompose complex BIM data into machine-interpretable components. This enables robots to not only see but understand their built environment, significantly improving object recognition and task execution in construction and facility management. Although early in its citation trajectory, this work has already garnered 3 citations, signaling its growing influence in the field. Ma’s research is critical for advancing smart construction, where robots must navigate and interact with dynamic, information-rich spaces. By fusing BIM’s structured data with robotic vision, he is laying the groundwork for more autonomous, efficient, and safe building operations—a key step toward the fully automated construction sites of the future.

Research Focus

Key Achievements

1
H-Index
1
Papers
3
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
Component-based BIM-semantic web integration for enhanced robotic visual perception
3 citations · 2025
📈 Most Prolific Year: 2025 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: China Academy of Building Research

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago