Shijie Qin

Shanghai Jiao Tong University, Beijing Academy of Artificial Intelligence, Chinese Academy of Sciences

Papers

Total Citations

H-Index

About

Shijie Qin is pioneering the intersection of chaos theory, biomechanics, and human-robot interaction, with a focus on developing intelligent systems that bridge the physical and digital worlds. His work spans from fundamental explorations of nonlinear dynamics—where his 2022 paper on "ultra-chaos" in mobile robots (29 citations) introduced a new framework for understanding disorder beyond traditional chaotic systems—to applied engineering for human-machine collaboration. A key contribution is his hierarchical optimization approach for personalized musculoskeletal modeling, which uses surface electromyography (sEMG) to tailor motion estimation to individual physiology, addressing the critical limitation of generic models in human-computer interaction (2024, 14 citations). In the emerging field of the Industrial Metaverse, Qin has proposed a hybrid controller for musculoskeletal robots that enhances flexibility and robustness in manufacturing lifting tasks (2024, 13 citations), demonstrating how bio-inspired design can outperform conventional rigid robots. His research is notable for seamlessly integrating theoretical depth with practical impact, offering scalable solutions for next-generation robotics and personalized rehabilitation. With a growing citation footprint, Qin is establishing himself as a leading voice in creating adaptive, human-aware systems for the future of work.