Derek Abbott
Papers
7
Total Citations
122
H-Index
6
About
Derek Abbott is a researcher whose work spans neuromorphic engineering, biologically inspired vision systems, and VLSI circuit design. Drawing on principles from nature, Abbott has made significant contributions to two interconnected domains: the computational modeling of biological neural systems and the development of insect-inspired artificial vision for collision avoidance applications. Among his most notable contributions is his work on the digital multiplierless realization of the Hindmarsh–Rose neuron model (2015, 64 citations), which advanced the efficient hardware implementation of coupled biological neural networks — work with far-reaching implications for treating neurological disorders and enhancing robotic performance. Complementing this, Abbott developed analog VLSI smart sensors that mimic insect visual processing, enabling compact, parallelized motion detection architectures suited for real-time obstacle avoidance. His 1995 smart microsensor paper garnered 19 citations and helped establish a biologically grounded, technology-independent paradigm for artificial vision systems. Abbott also contributed a compact analog VLSI model for Spike Timing Dependent Plasticity (2013), furthering neuromorphic learning circuit design. Across his career, his research consistently bridges biological insight and engineering innovation, offering practical pathways toward smarter, more efficient autonomous and neural computing systems.
Research Focus
Key Achievements
Top Papers
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- 3A micro-sensor based on insect vision13 citations · 2002
- 4A new compact analog VLSI model for Spike Timing Dependent Plasticity8 citations · 2013
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