Liming Jiang
Papers
2
Total Citations
9
H-Index
2
About
Liming Jiang is a rising researcher at the intersection of robotics, machine learning, and medical automation. His work centers on two critical challenges: advancing the kinematic modeling of cable-driven parallel robots (CDPRs) and enabling robots to learn complex, dexterous manipulation for surgical applications. In his highly cited 2024 paper, "CafkNet," Jiang introduced a novel GNN-empowered framework that directly tackles the notoriously difficult forward kinematics problem in CDPRs—a key bottleneck for their practical deployment. This work has already garnered 5 citations, signaling its impact on the field. Equally compelling is his research on robot-assisted surgery, where he developed a framework for learning target-directed skills and variable impedance control from interactive demonstrations. Applied to soft tissue puncture tasks, this work (4 citations) simplifies robotic control in percutaneous procedures by mimicking the dynamic interactions of the human arm. Jiang’s contributions are notable for their dual focus on foundational robotics theory and direct clinical translation, making him a promising figure in the next generation of intelligent robotic systems.
Research Focus
Key Achievements
Top Papers
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