Fan Xie

University of British Columbia

Papers

3

Total Citations

9

H-Index

2

About

Fan Xie is an emerging researcher at the forefront of construction robotics and intelligent automation, with a focus on integrating advanced technologies into modern building processes. His work bridges computer vision, machine learning, and robotic systems to transform conventional construction methodologies into smart, automated workflows. Xie's most notable contribution to date is his development of a novel computer vision and point cloud-based monitoring framework for full-scale robotized mobile cranes, published in 2024 and already accumulating 5 citations — a strong early indicator of relevance in this rapidly evolving field. This work addresses real-world construction monitoring challenges by combining sensory data with machine learning algorithms to enhance precision and efficiency on job sites. Building on this foundation, Xie has explored autonomous modular construction strategies that leverage deep learning and reinforcement learning, enabling robotic cranes to execute complex assembly tasks with minimal human intervention. His broader research agenda, reflected in his 2025 work on robotic construction and inspection, underscores a commitment to advancing automation, quality control, and sustainability in the building industry. For students and researchers interested in construction robotics, Xie represents a promising voice in shaping the future of intelligent infrastructure development.

Research Focus

Key Achievements

2
H-Index
3
Papers
9
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
A Computer Vision and Point Cloud-Based Monitoring Approach for Automated Construction Tasks Using Full-Scale Robotized Mobile Cranes
5 citations · 2024
📈 Most Prolific Year: 2025 (2 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: University of British Columbia

Top Papers

  1. 1
  2. 2
  3. 3

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago