Papers
13
Total Citations
968
H-Index
9
About
Jawad Nagi is a leading researcher at the intersection of computer vision, human-robot interaction, and swarm robotics. His work focuses on enabling intuitive, vision-based communication between humans and autonomous systems, particularly through hand gesture recognition. Nagi’s most influential contribution is his pioneering work on applying max-pooling convolutional neural networks to vision-based hand gesture recognition, a 2011 paper that has garnered over 648 citations and laid the groundwork for real-time human-robot interaction interfaces. He extended this research to multi-robot systems, introducing novel architectures like Convolutional Neural Support Vector Machines and developing distributed, incremental learning algorithms that allow robot swarms to cooperatively recognize gestures from human instructors. A significant achievement is his work on human-swarm interaction using spatial gestures, where he developed machine vision methods for operators to select and command individual or groups of UAVs using face pose estimates and hand gestures—a system demonstrated with Parrot drones. With over 950 total citations, Nagi’s research has profoundly impacted the fields of deep learning for gesture recognition and cooperative decision-making in multi-robot systems, bridging the gap between human intent and autonomous swarm behavior.
Research Focus
Key Achievements
Top Papers
- 1
- 2Human-swarm interaction using spatial gestures86 citations · 2014
- 3Human Control of UAVs using Face Pose Estimates and Hand Gestures77 citations · 2014
- 4
- 5Cooperative sensing and recognition by a swarm of mobile robots31 citations · 2012
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- 8Distributed consensus for interaction between humans and mobile robot swarms11 citations · 2012
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