Peer Neubert

Peer Neubert is a Professor at the University of Koblenz, appointed in October 2022, and previously a senior researcher (Dr.-Ing.) in the Automation Technology group at TU Chemnitz. His work lies at the intersection of autonomous robotics, computer vision, and machine learning, with particular expertise in place recognition in changing environments and hyperdimensional computing.

His research spans:

• Vector Symbolic Architectures and hyperdimensional representations for robotics,
• Visual place recognition robust to seasonal and illumination changes,
• Neurologically inspired navigation models (e.g., grid-cell representations),
• Deep learned and hand-crafted image descriptors for mobile robot localization,
• Efficient graph optimization and SLAM techniques.

Since 2010 he has published extensively in RSS, ICRA, CVPR, IEEE RA-L, and other premier venues, with a clear trend toward unsupervised, memory-efficient, and biologically inspired solutions. In 2022 he was nominated for the Heinz Maier-Leibnitz Prize by the Deutsche Forschungsgemeinschaft.

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