Papers
18
Total Citations
231
H-Index
10
About
Maram Sakr is a robotics and human-robot interaction researcher whose work spans augmented reality interfaces, learning from demonstration, and wearable sensing technologies. Her research is driven by a central mission: making collaboration between humans and robots more intuitive, effective, and safe across real-world applications. Sakr is perhaps best known for her pioneering work on augmented reality systems for human-robot collaboration in manufacturing environments. Her 2022 paper on AR head-mounted displays for shared physical workspaces has garnered 50 citations, establishing her as a leading voice in wearable interface design for industrial robotics. Complementing this, her investigations into multimodal systems combining AR, gestures, and tactile feedback further push the boundaries of intuitive robot programming. Her contributions to Learning from Demonstration (LfD) are equally significant, addressing critical gaps around demonstration quality, teacher training, and shared assistive control — work that collectively reflects a commitment to democratizing robotics for non-expert users. Her earlier research on Force Myography as a bio-signal sensing modality for human-machine interfaces, with over 25 combined citations across multiple studies, demonstrated her foundational interest in seamless physical human-robot communication. With over 200 total citations, Sakr's body of work meaningfully advances both the theory and practice of collaborative robotics.
Research Focus
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Top Papers
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- 6Quantifying Demonstration Quality for Robot Learning and Generalization17 citations · 2022
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