Papers
5
Total Citations
418
H-Index
5
About
Dr. Wei-Lung Mao is a leading researcher at the intersection of artificial intelligence, robotics, and environmental sustainability, with a primary focus on intelligent waste management and industrial automation. His most impactful work centers on applying deep learning and convolutional neural networks to solve real-world classification and detection challenges. His landmark 2020 paper, "Recycling waste classification using optimized convolutional neural network," has garnered 268 citations, establishing a foundational approach for automated sorting systems. Dr. Mao has further advanced this field with real-time waste detection networks (99 citations) and the development of an intelligent municipal solid waste sorter, demonstrating a clear trajectory from algorithm design to practical robotic implementation. Beyond environmental applications, he has made significant contributions to manufacturing quality control, notably integrating deep learning with a robot arm system for automated rim defect inspection. His work also extends to autonomous navigation, where he developed a novel 3D-to-2D LiDAR point cloud segmentation method for collision-free path planning, addressing critical limitations of vision-based algorithms under varying illumination conditions. Through these diverse yet interconnected contributions, Dr. Mao exemplifies how deep learning can bridge the gap between computational research and tangible, high-impact engineering solutions.
Research Focus
Key Achievements
Top Papers
- 1Recycling waste classification using optimized convolutional neural network268 citations · 2020
- 2Deep learning networks for real-time regional domestic waste detection99 citations · 2022
- 3
- 4Development of intelligent Municipal Solid waste Sorter for recyclables18 citations · 2023
- 5