Alister Hamilton

University of Edinburgh

Papers

6

Total Citations

71

H-Index

4

About

Alister Hamilton is a researcher whose career bridges neuromorphic computing, analog VLSI design, and bio-inspired robotics. His foundational contributions center on pulse stream neural network architectures implemented in custom silicon, most notably the EPSILON chipset — a landmark analog CMOS VLSI device capable of computing approximately 360 million synaptic connections per second. Developed through the early 1990s, EPSILON demonstrated the practical viability of pulse stream signaling for neural computation and incorporated innovative dynamic weight storage alongside amorphous silicon nonvolatile memory techniques. Hamilton subsequently advanced this platform with EPSILON II, improving electrical characteristics, interface flexibility, and architectural scalability, and established a broader system-level framework for analog neural computation in robotics applications. His later work took a distinctly bio-inspired direction, integrating MEMS wind sensors with analog VLSI circuits to replicate the cercal sensory system found in insects, culminating in a functioning insect-inspired robot. With his most cited work accumulating 27 citations and his EPSILON research garnering consistent recognition across nearly a decade of development, Hamilton's career represents a sustained and innovative effort to bring biologically plausible neural computation into real-world hardware systems.

Research Focus

Key Achievements

4
H-Index
6
Papers
71
Total Citations
12
Avg Citations/Paper
🏆 Most Cited Paper
Fabrication and characterization of a wind sensor for integration with a neuron circuit
27 citations · 2007
📈 Most Prolific Year: 2007 (2 Papers)
🤝 Key Collaborators: 16
🏛 Institutions: University of Edinburgh

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago