About

Yann Thoma is a pioneering researcher in bio-inspired hardware and reconfigurable computing, with a focus on spiking neural networks and complex systems simulation. His most influential work, "Hardware spiking neural network with run-time reconfigurable connectivity in an autonomous robot" (2003, 68 citations), introduced a cellular hardware implementation on a custom FPGA board that enabled real-time neural network reconfiguration for autonomous robotics. As a key contributor to the European Perplexus project, Thoma developed scalable hardware platforms—including the Ubichip, Ubidule, and MarXbot—that combine bio-inspired capabilities with agent-oriented programming to simulate large-scale, virtually-unbounded complex systems. His innovative multi-cellular electronic circuit (2004) demonstrated evolution and development capabilities, where identical cells contain the complete genetic description of the final system, mirroring biological development. Thoma’s work bridges hardware design and computational neuroscience, providing reconfigurable, bio-inspired architectures that allow researchers to study emergent behaviors in complex systems. His contributions have laid foundational hardware infrastructure for autonomous robotics and pervasive computing, enabling more adaptive and scalable simulations of natural and artificial systems.

Research Focus

Key Achievements

4
H-Index
5
Papers
122
Total Citations
24
Avg Citations/Paper
🏆 Most Cited Paper
Hardware spiking neural network with run-time reconfigurable connectivity in an autonomous robot
68 citations · 2003
📈 Most Prolific Year: 2003 (1 Papers)
🤝 Key Collaborators: 20
🏛 Institutions: International Institute for Management Development, École Polytechnique Fédérale de Lausanne, HES-SO University of Applied Sciences and Arts Western Switzerland

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago