Yuqin Liu

Beijing Institute of Graphic Communication, Peking University Shenzhen Hospital

Papers

Total Citations

H-Index

About

Yuqin Liu’s research bridges artificial intelligence and robotics to solve critical challenges in healthcare and intellectual property. Her primary contributions lie in two domains: developing intelligent robotic systems for high-risk medical tasks, and advancing patent analysis through semantic technologies. In healthcare robotics, Liu designed a surgical instruments sorting system that combines stereo vision with impedance control, automating a repetitive, infection-prone task traditionally performed manually by medical staff. She also created a dispensing robot for toxic chemotherapy drugs in pharmacy intravenous admixture services, directly addressing the dangers of manual handling of hazardous substances. Beyond robotics, Liu’s most impactful work is her 2019 paper on measuring patent similarity using SAO (Subject-Action-Object) semantic analysis, which has garnered 60 citations. This method offers a more nuanced approach to patent landscaping, enabling researchers and firms to identify technological overlaps and innovation trends with greater precision. While her robotic systems have lower citation counts, they represent practical, high-stakes applications in clinical settings. Liu’s work exemplifies how engineering innovation can enhance safety and efficiency in both healthcare operations and knowledge management.