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About

Maria Koutsombogera is a researcher whose work sits at the intersection of human-robot interaction, multimodal communication, and assistive robotics. She has made significant contributions to the development of frameworks that enable robots to understand and respond to complex human behavior through the integration of verbal and non-verbal signals, gesture, and multisensory data analysis. Her most influential work centers on the MOBOT project, an assistive robotic platform designed to support elderly users through proactive, adaptive, and cognitively aware interaction. Her 2016 paper on the MOBOT human-robot interaction model and user evaluation process has accumulated 23 citations, reflecting strong community engagement with her approach to grounding communication models in real-world user feedback. Alongside this, her contributions to multimodal and multisensory behavior analysis have helped establish richer semantic frameworks for interpreting human actions in robotic contexts. Koutsombogera has also explored educational robotics, examining how multiparty spoken dialogue and multimodal cues can be leveraged in tutoring robot scenarios. This breadth — spanning eldercare robotics, corpus development, and pedagogical applications — demonstrates a sustained commitment to making human-robot communication more natural, inclusive, and contextually intelligent. Her work is particularly valuable for researchers building socially aware robotic systems.