Minh Phung Dang
Papers
5
Total Citations
36
H-Index
4
About
Minh Phung Dang is a researcher specializing in intelligent design optimization, compliant mechanisms, and robotic systems, with a particular focus on bridging computational intelligence with precision engineering. His work addresses critical challenges in robotics, automation manufacturing, and biomedical micromanipulation, where rigid robotic systems fall short due to complex assembly and mechanical limitations. Dang's most influential contributions center on applying hybrid optimization techniques — combining finite element methods (FEM), neural-fuzzy systems, metaheuristic algorithms, and machine learning — to develop high-performance mechanical components. His 2022 study on rotary joint structural optimization, his most cited work with 13 citations, exemplifies this approach, integrating water cycle–moth flame algorithms with FEM for robotics manufacturing. His research on 3D-printed grippers for biomedical applications (10 citations) and topology-optimized robotic graspers (6 citations) demonstrates a consistent drive to advance microassembly and cell-manipulation technologies. Notably, Dang has also contributed to XYθ mobile microrobotic platform design for polishing robots, leveraging artificial neural networks and teaching-learning-based optimization. With a concentrated publication record predominantly from 2022, his work has rapidly accumulated recognition, reflecting the growing relevance of intelligent computational methods in next-generation robotics and precision bioengineering.
Research Focus
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Top Papers
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