Duhwan Mun
Papers
3
Total Citations
62
H-Index
2
About
Duhwan Mun is a researcher whose work spans the intersection of computer-aided design, deep learning, and advanced manufacturing systems. His most significant contribution to date is his 2021 paper introducing a dataset and deep learning-based methodology for reconstructing three-dimensional CAD models of mechanical parts containing machining features — a technically demanding problem with far-reaching applications in reverse engineering, 3D object recognition, robotic mapping, and industrial automation. This work has garnered 57 citations, reflecting its utility and influence within the CAD and computer vision communities. More recently, Mun has extended his research focus toward the emerging paradigm of Industry 5.0, proposing the novel Human and Humanoid-in-the-Loop (HHitL) ecosystem framework. This work addresses the growing imperative for manufacturing systems that are not only intelligent but also human-centric, resilient, and sustainable — integrating both human workers and humanoid robots into cohesive operational loops. Though still early in its citation trajectory, this line of inquiry positions Mun at the forefront of next-generation manufacturing philosophy. His evolving portfolio demonstrates a researcher committed to bridging foundational computational techniques with transformative visions for the future of industry.
Research Focus
Key Achievements
Top Papers
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