Papers
32
Total Citations
479
H-Index
10
About
Ayoub Al-Hamadi is a prominent researcher whose work sits at the intersection of computer vision, human-robot interaction (HRI), and robotic perception. Based at a leading research institution, he has made significant contributions to gaze estimation, visual SLAM, face recognition, and multimodal interaction systems that bridge the gap between humans and intelligent machines. Al-Hamadi's most cited work, "L2CS-Net" (2023, 105 citations), introduced a fine-grained gaze estimation framework using convolutional neural networks, advancing applications in virtual reality and human-robot interaction. His substantial body of HRI research — including the widely recognized "Robots and Wizards" study (2020, 56 citations) and the RoSA system (2022, 52 citations) — has systematically explored how humans naturally communicate with robots through speech, gestures, and gaze. His contributions to visual SLAM, particularly in dynamic environments, have strengthened the navigational capabilities of mobile robots. What distinguishes Al-Hamadi's research is its consistent focus on real-world applicability and safety, developing intuitive interfaces such as Robo-HUD for contactless industrial robot operation. With over 380 combined citations across his top works, his research continues to shape the future of intelligent, perceptive robotic systems.
Research Focus
Key Achievements
Top Papers
- 1L2CS-Net : Fine-Grained Gaze Estimation in Unconstrained Environments105 citations · 2023
- 2
- 3Robots and Wizards: An Investigation Into Natural Human–Robot Interaction56 citations · 2020
- 4
- 5Multimodal Engagement Prediction in Multiperson Human–Robot Interaction24 citations · 2022
- 6Face Recognition and Tracking Framework for Human–Robot Interaction22 citations · 2022
- 7
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- 9SLAM-Based Multistate Tracking System for Mobile Human-Robot Interaction13 citations · 2020
- 10Pixel-Wise Motion Segmentation for SLAM in Dynamic Environments11 citations · 2020