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About

Mark Adamik is a researcher at the intersection of human-robot interaction (HRI) and robotic perception, with a focus on building trustworthy and explainable autonomous systems. His major contributions span two critical areas: understanding how robot design and communication affect human trust, and enhancing robotic perception through structured knowledge. In his highly cited 2021 work (11 citations), Adamik demonstrated that personalizing a robot’s appearance significantly alters user trust, challenging the assumption that trust measurements always align with actual behavior. He further explored this in 2022 (5 citations), showing that providing users with textual or graphical explanations during collaborative tasks improves both trust and task performance. More recently, Adamik has advanced robotic perception by developing large-scale knowledge graphs and ontologies—such as ORKA—that enable robots to semantically link perceived entities to background knowledge, making their decision-making more robust and context-aware. His 2024 papers on perceived-entity linking and knowledge acquisition (each with 2 citations) represent foundational steps toward machines that can truly understand their environment. Adamik’s work is vital for applications in elder care, rehabilitation, and collaborative manufacturing, where safe, transparent, and intelligent robot behavior is paramount.