Ramy Sweidan

Papers

Total Citations

H-Index

About

Ramy Sweidan is a roboticist whose research focuses on dexterous manipulation and sensorimotor learning for humanoid robots. His most-cited work, "Learning to slide a magnetic card through a card reader" (2012, 14 citations), addresses a deceptively complex challenge in robotic manipulation: handling small, flexible, and partially occluded objects. In this study, Sweidan demonstrated how an upper-torso humanoid robot could learn to perform a precise card-swiping motion through trial-and-error, overcoming issues of visual occlusion and the card’s inherent flexibility. This contribution highlights his broader interest in enabling robots to interact with everyday objects in unstructured environments, bridging the gap between rigid, pre-programmed actions and adaptive, learned behaviors. While his citation count reflects a focused, niche contribution, the work is notable for its practical approach to a real-world manipulation problem—one that requires fine motor control and real-time adaptation. Sweidan’s research is particularly relevant for students and engineers working on humanoid robotics, tactile sensing, and learning from demonstration, offering a clear example of how robots can acquire skills that humans perform effortlessly but machines find extraordinarily difficult.