Nashwa El-Bendary

Arab Academy for Science, Technology, and Maritime Transport

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About

Nashwa El-Bendary is a leading researcher at the intersection of robotics, autonomous navigation, and human-robot interaction. Her work primarily focuses on enabling robots to perceive and operate intelligently in complex, real-world environments. A key contribution is in the domain of place recognition for autonomous systems, where she developed a semantics-enhanced discriminative descriptor learning method for LiDAR-based place recognition (2024, 11 citations), significantly improving a robot’s ability to localize itself in large-scale spaces. She has also advanced multi-sensor fusion for robust odometry and mapping, as demonstrated by her work on GV-iRIOM, a system integrating GNSS, visual, and 4D radar data for navigation in challenging, large-scale environments (2025). Beyond spatial perception, El-Bendary tackles critical challenges in collaborative robotics. Her notable work on a multimodal deep learning model for classifying human handover motions (2022, 2 citations) addresses a fundamental task for human-robot collaboration: enabling robots to understand and respond appropriately to different types of object transfers. This research is vital for creating safer and more intuitive interactions between humans and robots in shared workspaces.