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About

Rossitza Setchi is a distinguished researcher whose work spans reconfigurable manufacturing systems, human-robot interaction, and autonomous robotics. Her early contributions established foundational frameworks for reconfigurability in manufacturing — defining it as the capacity to repeatedly and cost-effectively restructure system components — a review that has garnered over 127 citations and remains a key reference in the field. Her research subsequently evolved toward intelligent robotics, with significant contributions to automated task planning for service robots, semantic knowledge representation, and common-sense reasoning in domestic environments. Setchi is perhaps best known for pioneering the concept of Explainable Robotics, introducing a research agenda focused on enabling robots to generate meaningful explanations during human-robot interactions, a paper that has already accumulated 89 citations since 2020. Her work on hierarchical reinforcement learning for multistep robotic manipulation (88 citations) further demonstrates her impact on advancing autonomous systems. Through projects such as the European SRS initiative, she has bridged theoretical research with real-world deployment of personal assistant robots. More recently, her investigations into human intention recognition and gaze trajectory prediction reflect a sustained commitment to making robots more socially and contextually aware — essential qualities for next-generation human-robot teaming.