Hatem A. Rashwan
Papers
5
Total Citations
188
H-Index
4
About
Hatem A. Rashwan is a computer vision and robotics researcher whose work sits at the intersection of deep learning, autonomous systems, and robot perception. He is best known for his influential 2022 review on monocular depth estimation using deep learning, which has accumulated an impressive 156 citations and stands as a key reference for researchers navigating the rapidly evolving landscape of depth perception in autonomous vehicles and robotics. Beyond this foundational survey, Rashwan has made meaningful contributions to practical implementation, developing efficient deep learning-based semantic mapping approaches tailored for resource-limited mobile robots — addressing a critical bottleneck in real-world deployment. His technical depth extends to multi-scale deep architectures enhanced with curvilinear saliency features for improved depth map estimation. Rashwan also demonstrates a broad systems-level perspective, with work spanning classical control theory — including PID and fuzzy logic systems for inverted pendulum stabilization — and innovative sensor applications, such as leveraging Dynamic Active-Pixel Vision Sensors (DAVIS) for real-time slip detection. Together, his portfolio reflects a researcher committed to bridging theoretical advances in perception with practical robotics engineering challenges.
Research Focus
Key Achievements
Top Papers
- 1Monocular Depth Estimation Using Deep Learning: A Review156 citations · 2022
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