Vedran Tunukovic
Papers
3
Total Citations
31
H-Index
2
About
Vedran Tunukovic is pioneering the next generation of non-destructive evaluation (NDE) for advanced composite materials, with a sharp focus on transforming how the aerospace industry inspects Carbon Fibre Reinforced Plastics (CFRPs). His core research sits at the intersection of machine learning, human-machine collaboration, and ultrasonic phased array testing. In his highly cited 2024 study (25 citations), Tunukovic systematically benchmarked object detection algorithms for automated ultrasonic data analysis, establishing a critical performance baseline for AI-driven defect identification in CFRPs. He further advanced the NDE 4.0 paradigm with his 2025 work on collaborative automation strategies, addressing the persistent bottleneck of manual data interpretation by designing intelligent systems that augment, rather than replace, human expertise. Most recently, his comparative assessment of out-of-plane ply waviness (2026) integrated Eddy Current Array, ultrasonic, and other modalities to evaluate a key failure mechanism in composite structures. By coupling rigorous experimental validation with cutting-edge AI, Tunukovic is not only improving inspection reliability but also laying the groundwork for fully autonomous, data-driven quality assurance in high-stakes manufacturing environments.
Research Focus
Key Achievements
Top Papers
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