Moslem Yousefi

Islamic Azad University Roudehen Branch, Universiti Tenaga Nasional

Papers

Total Citations

H-Index

About

Moslem Yousefi is a researcher whose work bridges the frontiers of intelligent robotics and human-machine interaction. His primary research areas include motion path planning for mobile robots and the development of lightweight, high-accuracy methods for gesture recognition using surface electromyography (sEMG). Yousefi’s major contributions are twofold: he advanced autonomous navigation in unknown environments through a comprehensive review of mobile robot path planning, a foundational work that has garnered 24 citations and remains a key reference for researchers tackling dynamic, hazardous settings like toxic waste disposal or bomb defusal. More recently, he developed a highly accurate, lightweight deep learning model for sEMG-based gesture recognition (29 citations), enabling efficient, real-time control of prosthetic and robotic systems. This work demonstrates his commitment to practical, deployable AI solutions. Yousefi’s impact is evident in the sustained relevance of his research, which informs both industrial automation and assistive technologies. His achievements reflect a rare ability to synthesize complex theoretical challenges—such as navigating unknown terrains—with cutting-edge deep learning applications, making his contributions valuable for students and engineers alike.