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About

Katharina Morik is a prominent researcher whose work sits at the intersection of machine learning, robotics, and knowledge representation. Her scholarship has focused primarily on enabling mobile robots to learn meaningful concepts directly from sensory experience — a challenge that bridges the gap between raw perception and higher-level symbolic reasoning. Morik's most influential contribution, "Learning Concepts from Sensor Data of a Mobile Robot" (1996), has accumulated 45 citations and established her as a key figure in robot learning research. This work, alongside her 1999 book *Making Robots Smarter: Combining Sensing and Action through Robot Learning*, reflects her sustained commitment to integrating sensing and action as the central paradigm for intelligent robotic behavior. The book synthesizes theoretical and practical perspectives on how robots can learn from and adapt to their environments in real time. Her additional publications explore incremental signal-to-symbol processing, grounded concept formation, and tailoring learned representations to varying task demands — collectively advancing the vision of robots that reason in human-understandable terms. Through these contributions, Morik helped lay conceptual groundwork for modern embodied AI, making her research particularly valuable for students exploring autonomous systems and cognitive robotics.