M. Hashem Shullar

King Fahd University of Petroleum and Minerals

Papers

Total Citations

H-Index

About

M. Hashem Shullar is a researcher focused on advancing autonomous navigation for robots and drones. His work addresses critical challenges in enabling self-sufficient operations, particularly through improvements in monocular depth estimation—a key technology for spatial understanding without expensive sensors. His most cited paper, "Enhancing Monocular Depth Estimation via Image Pre-processing Techniques" (2022), has garnered 3 citations and proposes novel pre-processing methods to boost depth perception accuracy, directly supporting safer and more efficient autonomous flight and movement. By tackling the limitations of single-camera systems, Shullar contributes to reducing human intervention in drones and robots, enhancing their operational reliability in real-world applications. His research sits at the intersection of computer vision and robotics, aiming to bridge the gap between current capabilities and the demands of fully autonomous systems. With a focus on practical, low-cost solutions, Shullar’s work holds promise for scaling autonomous technologies across industries like logistics, surveillance, and environmental monitoring.