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About

Agnes Swadzba is a versatile robotics researcher whose work spans human-robot interaction, robot programming, autonomous navigation, and scene understanding. She has made significant contributions to the field of social robotics, most notably through her influential investigations into how users perceive and envision applications for social robots. Her 2007 studies, drawing on responses from over 100 participants, helped establish a systematic framework for classifying meaningful robot applications — work that has collectively garnered over 80 citations and shaped thinking about robot deployment in everyday contexts. Swadzba's most cited contribution — a 2013 user study on kinesthetic teaching of redundant robots (100 citations) — addresses the practical challenge of programming physically flexible robots intuitively, a problem she continued tackling through her development of assisted gravity compensation techniques. These methods meaningfully lower the barrier for non-expert robot programming. Her technical breadth is further demonstrated through work on 3D sensor-enhanced navigation, dynamic scene analysis, and room categorization using spatial features — research that advances autonomous robot perception in real-world environments. Across her career, Swadzba's work reflects a consistent commitment to making robots more practical, intuitive, and socially integrated, bridging rigorous engineering with genuine consideration for the humans who interact with these systems.