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About

Norbert Domcsek is a robotics and computational neuroscience researcher whose work bridges biological intelligence and autonomous systems, with a particular focus on insect-inspired visual navigation and adaptive robotics. Based at the University of Sussex, Domcsek has made significant contributions to understanding how simple neural architectures can enable robust navigation in real-world environments, drawing inspiration from the remarkable navigational abilities of insects such as ants. His most influential work explores familiarity-based navigation strategies, demonstrating that single-layer neural networks encoding visual memories can guide autonomous robots along real-world routes with minimal computational overhead — a breakthrough with major implications for power-constrained robotics. His research into spiking neural network models of insect mushroom bodies further advances our understanding of how biological memory systems underpin complex learned behaviours. Domcsek has also contributed to the broader field of evolutionary and bio-inspired adaptive robotics, with that collaborative work accumulating 36 citations since 2021. Across his publication record, Domcsek's research consistently champions the principle that nature's elegant, resource-efficient solutions can directly inform next-generation autonomous systems, making him a compelling voice at the intersection of neuroscience, artificial intelligence, and robotics.