Joana Dias
Papers
2
Total Citations
14
H-Index
2
About
Joana Dias is a researcher at the forefront of industrial automation and human-robot collaboration, with a primary focus on integrating advanced sensing and intuitive teaching methods into manufacturing processes. Her work addresses critical challenges in automating complex, repetitive tasks, particularly in the automotive and biomedical sectors. Dias’s major contributions include a pioneering comparative analysis of 3D sensors for robotic bolt-tightening operations, which provides a systematic framework for selecting optimal vision systems to enhance robot adaptability in dynamic assembly lines. This study, her most cited work with 9 citations, directly informs the design of more flexible and reliable automation solutions. Additionally, she has advanced human-robot interaction through a kinesthetic teaching approach for automating micropipetting tasks, demonstrating how operators can intuitively program robots by physically guiding them, thereby reducing the skill barrier for lab automation. With a growing citation record, Dias’s research is instrumental in bridging the gap between human expertise and robotic precision, offering practical, data-driven pathways to safer, more efficient, and accessible automation across industries.
Research Focus
Key Achievements
Top Papers
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