Papers
9
Total Citations
1,129
H-Index
9
About
Kristin Dana is a leading researcher in computer vision and robotics, with a focus on automated infrastructure inspection and material recognition. Her major contributions include pioneering algorithms for detecting cracks on concrete bridges—her 2014 paper on the STRUM algorithm has garnered 461 citations—and developing ground-penetrating radar (GPR) analysis for robotic bridge deck evaluation, cited 130 times. Dana’s work on ground terrain recognition, particularly the Deep Encoding Pooling Network (DEP) introduced in 2018, has been cited 146 times and is instrumental for robot navigation and outdoor localization. She also contributed to the advancement of mobile optical communications and context-aware operating theaters. Notable achievements include leading the development of an autonomous bridge deck inspection robotic system (2017, 120 citations), which addresses critical safety concerns for aging infrastructure. Dana’s research bridges computational appearance modeling and real-world applications, with over 1,000 total citations across her most-cited works. Her innovative approach to texture manifolds and differential viewpoints continues to influence fields from structural health monitoring to autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1Automated Crack Detection on Concrete Bridges461 citations · 2014
- 2Deep Texture Manifold for Ground Terrain Recognition146 citations · 2018
- 3Automated GPR Rebar Analysis for Robotic Bridge Deck Evaluation130 citations · 2015
- 4Development of an autonomous bridge deck inspection robotic system120 citations · 2017
- 5Challenge116 citations · 2010
- 6
- 7Differential Viewpoints for Ground Terrain Material Recognition31 citations · 2020
- 8Capturing Computational Appearance: More than meets the eye12 citations · 2016
- 9Deep Texture Manifold for Ground Terrain Recognition10 citations · 2018