Asif Shahriyar Sushmit

Bangladesh University of Engineering and Technology

Papers

Total Citations

H-Index

About

Asif Shahriyar Sushmit is a researcher in robotics and intelligent control systems, with a focus on human-robot interaction through natural and intuitive interfaces. His work centers on developing neural network-based control mechanisms that allow robots to respond to voice commands and human gestures, aiming to make industrial automation more accessible and user-friendly. In his most cited paper (7 citations), he designed a Bangla voice-controlled robotic gripper arm, demonstrating how neural networks can interpret speech to control mechanical actions. His complementary work on gesture-controlled grippers (2 citations) integrates image processing with neural networks, enabling robots to follow hand movements and visual feedback. Together, these contributions address key challenges in human-robot collaboration, particularly for non-English speaking users and industrial settings. Sushmit’s research represents an important step toward low-cost, adaptable robotic systems that can be operated without specialized training, bridging the gap between advanced automation and everyday usability. His work continues to influence the development of more natural control interfaces in robotics.