Regular biography
Wulfram Gerstner is a Full Professor at the École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the Department of Computer Science (CS). His research focuses on computational neuroscience, particularly the mathematical modeling of neurons and neural networks, with an emphasis on neuronal dynamics and learning mechanisms. He teaches courses on computational neurosciences, learning in neural networks, and behavioral neuroscience. Gerstner has contributed to several publications in top-tier journals, including Nature Communications and Science, and supervises PhD students at EPFL.
Scholar-generated biography
Wulfram Gerstner is a leading figure in theoretical neuroscience, focusing on the development of mathematical models to understand neuronal dynamics and plasticity. His research spans from single-neuron behavior to population-level activity, with an emphasis on spike timing-dependent plasticity (STDP) and its role in learning and memory. Gerstner's work explores how neural networks process information and how synaptic plasticity contributes to cognitive functions. His publications include studies on spiking neuron models, Hebbian learning, and the mathematical formulations of learning rules. He has also investigated the application of brain signals to control robotic systems, highlighting the intersection of neuroscience and engineering.