Lionel Tarassenko

University of Oxford, Science Oxford

Papers

9

Total Citations

370

H-Index

7

About

Lionel Tarassenko is a pioneering researcher whose work sits at the intersection of neuromorphic hardware, analogue VLSI systems, and applied artificial intelligence. His most influential contributions centre on pulse-stream neural networks — a technique representing neural states as sequences of pulses to efficiently blend analogue and digital computation on chip. His 1991 paper on this approach has garnered over 200 citations, establishing it as a foundational reference in the field of hardware neural networks. Tarassenko also made significant advances in analogue computation for robotics, developing innovative methods for robot path planning using resistive grids and electric potential fields, and demonstrating real-time autonomous navigation through custom VLSI neural network modules. His work on on-chip learning schemes further addressed the practical challenges of implementing adaptive computation within the constraints of analogue hardware. More recently, his research has expanded into healthcare, exploring how artificial intelligence can enable more informed clinical care — reflecting a career-long commitment to translating computational intelligence into real-world applications. Across robotics, neuromorphic engineering, and health informatics, Tarassenko's body of work represents a sustained and impactful effort to make intelligent computation practical, efficient, and deployable.

Research Focus

Key Achievements

7
H-Index
9
Papers
370
Total Citations
41
Avg Citations/Paper
🏆 Most Cited Paper
Pulse-stream VLSI neural networks mixing analog and digital techniques
201 citations · 1991
📈 Most Prolific Year: 1991 (3 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: University of Oxford, Science Oxford

Top Papers

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    Real-time autonomous robot navigation using VLSI neural networks
    19 citations · 1990
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Key Collaborators

Contact & Links

Available for collaboration
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