Keith Worden
Papers
7
Total Citations
131
H-Index
5
About
Keith Worden is a pioneering figure at the intersection of structural health monitoring (SHM), non-destructive evaluation (NDE), and machine learning. His research fundamentally advances how we detect, localize, and identify damage in engineering structures—from bridges and aircraft to pipelines. Worden’s major contributions include developing probabilistic and Bayesian frameworks for autonomous robotic inspection, enabling intelligent data collection and robust outlier analysis that dramatically improves damage detection reliability. His highly cited 2020 paper, “Machine learning at the interface of structural health monitoring and non-destructive evaluation” (58 citations), provides a landmark synthesis of these fields, clarifying their distinct roles while showing how machine learning can unify them. Worden has also pioneered the simulation and implementation of reconfigurable robotic “remote sensing agents” for ultrasonic Lamb wave inspection, work that addresses the practical challenges of automating NDE in hazardous or inaccessible environments. With a career spanning foundational theory to real-world robotic deployment, Worden’s work is essential reading for anyone interested in smart infrastructure, autonomous inspection, or the future of non-destructive testing.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4A PROBABILISTIC APPROACH TO ROBOTIC NDE INSPECTION6 citations · 2010
- 5
- 6
- 7