Dipayan Saha

Bangladesh University of Engineering and Technology

Papers

Total Citations

H-Index

About

Dipayan Saha is a researcher at the intersection of human-computer interaction, assistive robotics, and deep learning. His most cited work, "Deep Learning-Based Eye Gaze Controlled Robotic Car" (2018, 7 citations), pioneers a non-invasive, gaze-driven control system that enables motor-disabled individuals to operate a robotic vehicle using only eye movements. By integrating convolutional neural networks for real-time gaze estimation with autonomous navigation, Saha demonstrates how deep learning can transform assistive technology—offering a low-cost, hands-free alternative to traditional joystick or voice controls. This contribution is particularly impactful for safe car driving and rehabilitation robotics, where precise, intuitive interfaces are critical. Beyond this flagship study, Saha’s broader research explores gaze estimation as a diagnostic tool and a communication mode for those with severe motor impairments. His work has been cited in contexts ranging from autonomous robot control to human-computer interaction, reflecting its interdisciplinary reach. With a focus on practical, deployable solutions, Saha continues to advance the field of assistive AI, making technology more accessible and empowering for individuals with disabilities.