Surejya Suresh

Cochin University of Science and Technology

Papers

Total Citations

H-Index

About

Surejya Suresh is a researcher at the forefront of human-computer interaction (HCI), with a primary focus on developing accessible technologies through deep learning. Her most cited work, the 2019 paper "Sign Language Recognition System Using Deep Neural Network," has garnered 30 citations, establishing a foundational approach to bridging communication gaps between hearing and speech-impaired communities and digital systems. Suresh’s major contribution lies in addressing the limitations of conventional input devices by designing neural network architectures that interpret complex, dynamic hand gestures in real time. This work not only advances the field of assistive technology but also underscores the critical role of HCI in societal progress. Her research demonstrates a commitment to making technology more inclusive and intuitive, pushing beyond traditional keyboard-and-mouse interfaces. By leveraging deep neural networks for sign language interpretation, Suresh has opened new pathways for seamless, natural interaction between humans and machines. Her achievements highlight the transformative potential of AI in accessibility, inspiring further innovation in gesture-based control systems and inclusive design.