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Research Interests: Neuromorphic engineering

Neuromorphic engineering develops circuits that carry out computations in close resemblance to those carried out by neuronal hardware. Those systems are usually implemented as analog very large scale integrated (aVLSI) chips. Neuromorphic systems range from sensory input chips like silicon retinas and silicon cochleas to silicon neurons and networks of silicon neurons that learn to movement control chips on the output side.

S. Still, K. Hepp, and R. J. Douglas. Neuromorphic Walking Gait Control. IEEE Transactions on Neural Networks, Volume 17, Issue 2, pp. 496 - 508. 2006.

S. Still, B. Schölkopf, K. Hepp, and R. J. Douglas. Four-legged Walking Gait Control Using a Neuromorphic Chip Interfaced to a Support Vector Learning Algorithm. In Todd K. Leen, Thomas G. Dietterich, and Volker Tresp, editors, Advances in Neural Information Processing Systems 13, pp. 741--747, 2001. MIT Press.

S. Still. Walking gait control for four-legged robots. ETH (Swiss Federal Institute of Technology) Zuerich, Department of Physics, 2000.


Student Projects (499, 699) and thesis projects:

1. Learning chips
            Looking for a student who is interested in a collaborative project with G. Indiveri, ETH Zuerich.

2. Walking robots
            Movement control and co-ordination for legs and a spine.

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