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of the CDPR is analyzed. The results show that the proposed method can effectively predict the dynamic response interval of the CDPR under uncertainty, providing a theoretical basis for the reliability design of the CDPR. Sipan Li is a leading researcher in the field of cable-driven parallel robotics, with a focus on multi-objective optimization, adaptive control, and dynamic modeling. His work addresses critical challenges in the design and control of cable-driven parallel robots (CDPRs), which are prized for their high load capacity and large workspace but are hindered by complex dynamics and uncertainty. Li’s most cited paper (31 citations) introduces an adaptive particle swarm optimization algorithm for the optimal design of CDPRs, significantly improving convergence speed and solution accuracy. He has also pioneered adaptive fuzzy tracking control for vibration suppression in cable-driven hoisting robots (15 citations) and developed a rigid-flexible coupling model for hoisting robots that accounts for cable deformation and random loading (7 citations). His recent work on interval-based dynamic modeling (4 citations) provides a theoretical foundation for reliability design under uncertainty. Li’s research has direct applications in engineering fields such as construction, manufacturing, and logistics, where precise and robust robotic systems are essential.