Papers
5
Total Citations
30
H-Index
3
About
Caroline Vienne is a leading researcher at the intersection of non-destructive testing (NDT), industrial computed tomography (CT), and intelligent robotics for Industry 5.0. Her work is driven by a vision of flexible, human-centric automation, where robots and advanced imaging collaborate to ensure quality and safety. Vienne’s major contributions include developing fast algorithms based on Empirical Interpolation Methods (EIM) to optimize projection selection in sparse-view X-ray CT, a technique that dramatically reduces scan time while maintaining image fidelity—critical for high-throughput industrial inspection. Her most cited work (16 citations) demonstrates how a priori information can guide these algorithms for superior results. In parallel, she has pioneered the concept of the “Robot Companion” for Industry 5.0, creating intelligent, interactive robotic coworkers that adapt to novel tasks through modular architectures, moving beyond rigid automation. Her research on limited-angle CT trajectories for robotic inspection further showcases her ability to solve real-world constraints. With a growing citation impact and a focus on practical, deployable solutions, Vienne is shaping the future of smart manufacturing and collaborative robotics.
Research Focus
Key Achievements
Top Papers
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