Papers
2
Total Citations
9
H-Index
2
About
Fariha Haque is a robotics researcher whose work focuses on making human-robot interaction more intuitive and accessible. Her key research areas include neural network-based control systems, voice recognition technology, and gesture-controlled automation. Haque’s major contributions lie in designing low-cost, efficient robotic gripper arms that can be operated through natural human commands, bridging the gap between complex industrial machinery and user-friendly interfaces. Her most cited work, “Design of a voice controlled robotic gripper arm using neural networks” (2017), has garnered 7 citations and proposes a novel method for building a Bangla voice-controlled robotic mechanism—a significant step toward language-inclusive automation. In a complementary study, “Design of a gesture controlled robotic gripper arm using neural networks” (2017), she explores image processing and neural networks to enable gesture-based control with visual feedback, aiming to enhance industrial automation processes. Haque’s research is particularly notable for its emphasis on affordability and practicality, making advanced robotic control systems more accessible to developing industries. Her work demonstrates a clear commitment to democratizing automation technology through intelligent, user-centric design.
Research Focus
Key Achievements
Top Papers
- 1Design of a voice controlled robotic gripper arm using neural networks7 citations · 2017
- 2Design of a gesture controlled robotic gripper arm using neural networks2 citations · 2017