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About

Dong Qiang is a researcher at the forefront of collaborative robotics and intelligent automation, with a focus on enhancing human-robot interaction for small and medium-sized enterprises. His work bridges mechanical modeling and artificial intelligence, particularly through the development of digital twins for harmonic drive-based robot joints, enabling precise force estimation and performance simulation—critical for safe, adaptive manufacturing. His 2022 paper on dynamic modeling and digital twins has garnered 20 citations, reflecting its impact on advancing robot control and simulation. Additionally, Qiang contributes to lifelong learning in robotics, co-authoring a benchmark dataset for object recognition that supports continuous adaptation in dynamic environments. His research not only pushes the boundaries of robot dexterity and autonomy but also addresses real-world industrial needs, making him a key figure in the evolution of collaborative systems.