Harry Erwin
Papers
13
Total Citations
193
H-Index
7
About
Harry Erwin is a researcher whose work sits at the intersection of computational neuroscience, biologically inspired systems, and autonomous robotics, with a particular focus on auditory perception and sound source localisation. Over the course of his career, Erwin has made significant contributions to the development of robotic systems capable of mimicking the sophisticated acoustic processing found in biological organisms, drawing inspiration from the structure and function of the human auditory midbrain, including the inferior colliculus and superior olivary complex. His most influential work, "Robotic sound-source localisation architecture using cross-correlation and recurrent neural networks" (2009, 44 citations), exemplifies his signature approach of combining signal processing techniques with neural network architectures to enable robots to dynamically track sound sources in real time. Erwin has also advanced multimodal robot learning frameworks, exploring how robots can integrate multiple sensory modalities and learn through both demonstration and instruction. His biologically inspired spiking neural network models have opened new avenues for improving signal-to-noise ratios in socially interactive robots and extending localisation to three-dimensional space, including elevation detection. Collectively, his body of work has garnered over 180 citations, establishing him as a meaningful contributor to neuromorphic robotics and intelligent auditory systems.
Research Focus
Key Achievements
Top Papers
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- 2Towards multimodal neural robot learning40 citations · 2004
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