Papers
3
Total Citations
11
H-Index
3
About
Jiawei Ma is a researcher at the forefront of intelligent manufacturing and robotic automation, with a core focus on welding trajectory planning and computer vision. His major contributions lie in developing adaptive, vision-guided systems that overcome the limitations of traditional offline programming for large-scale industrial parts. In his 2025 work on handheld 3D scanning-based robotic trajectory planning, Ma introduced a method that generates accurate STL models from asymmetric profiles, enabling multi-layer multi-pass welding for large intersecting line workpieces—a breakthrough for parts with significant machining deviations. Complementing this, his dual-modal framework (2025) integrates 2D image recognition with 3D point cloud processing, enhancing robustness under complex conditions. Beyond manufacturing, Ma has innovated in medical diagnostics with his 2021 study on adaptable automated interpretation of rapid diagnostic tests using few-shot learning, improving point-of-care LFA accuracy. Though his papers have garnered modest early citations (3–4 each), their interdisciplinary impact—bridging robotics, deep learning, and healthcare—signals a promising trajectory. Ma’s work exemplifies how vision-based automation can transform both industrial welding and clinical diagnostics, making him a rising figure in applied AI and robotics.
Research Focus
Key Achievements
Top Papers
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