Shaikh Al Mahmud Bhuiyan

Bangladesh University of Engineering and Technology

Papers

Total Citations

H-Index

About

Shaikh Al Mahmud Bhuiyan is a researcher focused on the intersection of robotics, neural networks, and industrial automation. His most-cited work, "Design of a gesture controlled robotic gripper arm using neural networks" (2017), introduces an innovative, low-cost approach to robotic control by integrating image processing and neural networks for gesture-based commands. This design, comprising three modules, aims to enhance efficiency in industrial automation by enabling intuitive, visual-feed-driven manipulation. With 2 citations, this foundational contribution underscores his commitment to accessible, intelligent robotic systems. Bhuiyan’s research bridges practical engineering and advanced computational methods, offering scalable solutions for real-world manufacturing challenges. His work highlights the potential of neural networks to transform human-robot interaction, making automation more adaptable and cost-effective. As a researcher, he continues to explore how gesture recognition and AI can streamline industrial processes, positioning himself at the forefront of affordable, smart robotics.