Neuromorphic and Bioinspired Computing

Biological principles guide the design of neural architectures and learning systems. Research develops spiking networks, reservoir computing and wiring rules inspired by genetic organisation and spatial structure. Studies of excitation, inhibition and memory connect network dynamics with computational performance, while mismatch-tolerant learning explores how neural computation can remain robust under device variability.

• Spiking networks and reservoir computing
• Bioinspired wiring and network topology
• Learning dynamics and computational memory
• Mismatch-tolerant neuromorphic learning