Matthias U. Keysermann

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About

Matthias U. Keysermann is a researcher in cognitive robotics and human-robot interaction, with a focus on developing autonomous systems that can learn, remember, and respond emotionally. His work centers on computational models inspired by neuroscience, particularly the interaction between neural and endocrine systems, to create robots capable of emotional memory. His most cited paper, "Towards Autonomous Robots Via an Incremental Clustering and Associative Learning Architecture" (2014, 13 citations), proposes a framework for robots to learn incrementally and associate sensory inputs with actions, enabling more adaptive behavior. In "Emotional memories in autonomous robots" (2014, 6 citations), he advances a theoretical model that integrates emotion and memory, aiming to improve human-robot interaction by allowing robots to detect and respond to emotional changes. Keysermann also explores trust and confidentiality in human-robot relationships, as seen in "Can I trust you? Sharing information with artificial companions" (2012, 2 citations), where he investigates user preferences for information sharing with robot companions in office settings. His contributions bridge cognitive science and robotics, offering insights into how robots can become more socially aware and trustworthy companions.