John Stormont

University of New Mexico

Papers

2

Total Citations

10

H-Index

2

About

John Stormont is a researcher whose work sits at the intersection of structural health monitoring, transportation infrastructure preservation, and intelligent sensing systems. His research focuses on developing innovative approaches to detect structural vulnerabilities in aging infrastructure before they lead to catastrophic failures — a challenge of growing urgency as transportation networks worldwide continue to deteriorate beyond their original design lifespans. Among his most notable contributions is his work on remote tap-testing technologies, exploring how automated devices deployed via ground vehicles can efficiently assess the health of transportation infrastructure at scale. This work, which has garnered 8 citations since its 2022 publication, represents a meaningful step toward reducing the cost and danger associated with manual structural inspections. Complementing this, his 2021 research on machine learning-assisted crack detection for rockfall prevention demonstrates his commitment to applying emerging computational tools to real-world safety challenges, offering transportation agencies a proactive means of identifying unstable rock formations before they threaten lives or roadways. Stormont's research reflects a broader vision of smarter, safer infrastructure management — one where automation and data-driven techniques replace hazardous human inspections, ultimately protecting both workers and the traveling public.

Research Focus

Key Achievements

2
H-Index
2
Papers
10
Total Citations
5
Avg Citations/Paper
🏆 Most Cited Paper
Use of Remote Structural Tap Testing Devices Deployed via Ground Vehicle for Health Monitoring of Transportation Infrastructure
8 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: University of New Mexico

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago