Yufeng Lian
Papers
2
Total Citations
42
H-Index
2
About
Yufeng Lian is a leading researcher in rehabilitation robotics and intelligent vehicle control systems, whose work bridges the gap between human-robot interaction and automotive safety. His primary research areas include adaptive iterative learning control for rehabilitation robots, road adhesion coefficient identification, and human-in-the-loop control systems. Lian's most impactful contribution is his 2021 paper on a novel adaptive iterative learning control approach for lower limb rehabilitation robots in disturbance environments, which has garnered 35 citations and introduced a groundbreaking human-in-the-loop control pattern that enhances robot adaptability and patient safety during therapy. More recently, in 2024, he developed an improved MobileNet V3-based method for road adhesion coefficient identification, enabling real-time adjustment of automobile active safety systems to improve driving safety under complex conditions. This work, with 7 citations to date, demonstrates his versatility in applying deep learning to critical automotive challenges. Lian's research is characterized by its practical impact, directly addressing real-world problems in rehabilitation and autonomous driving, making him a notable figure in both biomedical engineering and intelligent transportation systems.
Research Focus
Key Achievements
Top Papers
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