David A. Guerra-Zubiaga
Papers
14
Total Citations
123
H-Index
5
About
David A. Guerra-Zubiaga is a prominent researcher whose work sits at the intersection of robotics, intelligent manufacturing, and Industry 4.0 technologies. His research spans industrial robotics, digital twins, computer vision, domain adaptation, and smart manufacturing systems, positioning him as a versatile contributor to the future of automated production and engineering education. Among his most recognized contributions is his investigation into energy consumption in industrial robots using Design of Experiment methodology (2020, 29 citations), offering actionable insights for more sustainable manufacturing aligned with Industry 4.0 goals. His comprehensive review of domain adaptation in computer and robotic vision (2023, 20 citations) has quickly become a valuable reference for researchers navigating machine learning challenges in real-world robotic deployments. Equally impactful is his work on low-cost digital twin frameworks bridging K–12 and higher education (2023, 18 citations), demonstrating a commitment to democratizing advanced manufacturing education. Guerra-Zubiaga has also advanced pick-and-place robotics through computer vision integration, developed an intelligent hexapod for airframe inspection using deep learning, and explored soft robotics for remote medical ultrasound applications. His interdisciplinary portfolio, accumulating over 110 citations across a decade, reflects both technical depth and a genuine drive to translate cutting-edge research into practical industrial and educational solutions.
Research Focus
Key Achievements
Top Papers
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- 2An In-Depth Analysis of Domain Adaptation in Computer and Robotic Vision20 citations · 2023
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- 10Digital Factory: Simulation Enhancing Production and Engineering Process3 citations · 2018