Md. Abdur Rahman
Papers
2
Total Citations
7
H-Index
2
About
Md. Abdur Rahman is a researcher at the forefront of applied robotics and AI-driven public health solutions. His work spans two distinct yet impactful domains: developing intelligent systems for disease vector control and engineering novel robotic mechanisms for industrial applications. In his highly cited 2021 study, "Detection of Mosquito Larvae Using Convolutional Neural Network," Rahman tackled the global challenge of mosquito-borne diseases by proposing a non-chemical, AI-based approach to identify larvae—offering a more targeted alternative to traditional adulticide methods. This work, with 5 citations, demonstrates his commitment to leveraging deep learning for environmental monitoring. Simultaneously, Rahman has made notable contributions to robotics engineering. His 2021 paper on a "Vertical Climbing Robot With High Mobility For Flat And Spherical Surfaces" introduced a novel mechanism designed for heavy lifting on challenging geometries, achieving 2 citations for its innovative design. By bridging computer vision and mechanical design, Rahman’s research exemplifies a versatile approach to solving real-world problems—from public health to infrastructure maintenance—showcasing his ability to integrate AI with practical, high-mobility robotic systems.
Research Focus
Key Achievements
Top Papers
- 1Detection of Mosquito Larvae Using Convolutional Neural Network5 citations · 2021
- 2