Papers
3
Total Citations
25
H-Index
3
About
Liang Ye is a researcher at the intersection of artificial intelligence, robotics, and medical engineering, with key contributions in point cloud processing, robotic manipulation, and artistic automation. His work on LA-Net, a novel LSTM and attention-based method for point cloud down-sampling, addresses critical limitations in learning-based sampling by ensuring sampled points remain within the original set—a breakthrough with 10 citations that enhances downstream tasks in 3D vision. In medical robotics, Ye led the design and control of a forming robot for internally fixed titanium alloy strips, achieving 9 citations by solving the challenge of bending biocompatible materials to fit surgical supports, improving precision in orthopedics. He also developed the CCD-BSM composite-curve-dilation brush stroke model for robotic Chinese calligraphy (6 citations), merging artistic expression with robotic control. Ye’s impact spans from advancing 3D data processing to enabling safer surgical procedures and creative robotics, demonstrating a rare ability to bridge theoretical innovation with practical, life-saving applications. His work continues to inspire students and researchers exploring the frontiers of intelligent systems and human-robot interaction.
Research Focus
Key Achievements
Top Papers
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