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About

Danica Kragic is a prominent robotics researcher whose work spans visual perception, robotic manipulation, and machine learning for embodied intelligent systems. With early contributions dating back to her influential 2002 work on visually guided manipulation tasks—now with 49 citations—Kragic has consistently pushed the boundaries of how robots perceive and interact with their environment. Her research addresses some of the most challenging frontiers in modern robotics, including transfer learning for intelligent agents, tactile sensing, and the manipulation of deformable objects such as textiles. Her 2024 review on transfer learning in robotics (36 citations) synthesizes critical promises and obstacles in building robots that generalize knowledge across novel contexts, while her equally timely review on robotic cloth manipulation tackles the unique complexities posed by deformable materials across healthcare, industrial, and household settings. Kragic's work also extends into formal task planning through spatio-temporal logic, out-of-distribution robustness in learned policies, and low-cost teleoperation with haptic feedback. Collectively, these contributions reflect a research vision centered on making robots more adaptive, reliable, and practically deployable. Her broad and growing citation record underscores her significant influence on the international robotics and AI research community.