Safa Munir
Papers
1
Total Citations
13
H-Index
1
About
Dr. Safa Munir is making impactful strides at the intersection of assistive technology and deep learning, with a primary focus on bridging communication gaps for the hearing impaired. Her most cited work, "Robot Assist Sign Language Recognition for Hearing Impaired Persons Using Deep Learning" (2023), has garnered 13 citations and exemplifies her commitment to developing accessible, real-world solutions. In this study, she pioneered a system that integrates robotic assistance with deep neural networks to translate sign language into comprehensible output, thereby empowering deaf individuals to communicate more fluidly with the hearing world. This contribution not only advances the field of human-robot interaction but also addresses a critical social need for inclusive communication technologies. Dr. Munir’s research demonstrates a rare blend of technical rigor and humanitarian purpose, positioning her as a rising voice in assistive AI. Her work serves as an inspiring model for students and researchers seeking to apply cutting-edge machine learning to solve pressing societal challenges, proving that impactful engineering can—and should—be deeply human-centered.
Research Focus
Key Achievements
Top Papers
- 1