Contact Tim here:
Tim C Kietzmann
Tim obtained his PhD in Cognitive Science (Dr. rer. nat.) working towards a better understanding of visual processing in humans by combining machine learning and cognitive neuroscience. He was supervised by Peter König (University of Osnabrück), and Frank Tong (Vanderbilt University). After a few years at the MRC Cognition and Brain Sciences Unit of the University of Cambridge, where he worked with Nikolaus Kriegeskorte, he started his own lab at the Donders (Radboud University).
Contact Adrien here:
Adrien studied neuroscience and physics at EPFL, and recently completed his Ph.D. in Neuroscience there under the supervision of Michael Herzog. His interests include neural computations in recurrent networks, in particular for vision, and, more broadly, understanding how and when different computational properties emerge in neural networks. He has also worked on theoretical issues in consciousness science.
Contact Hannes here:
Johannes studied psychology and neuroscience at Hamburg, Philadelphia, and Maastricht. He recently completed his PhD in neuroscience at Cambridge, UK, under supervision of Tim Kietzmann and Nikolaus Kriegeskorte. His research focuses on computational models of the human visual cortex. During his PhD he investigated representational similarities in deep neural network (DNN) models and created a DNN training set specifically designed for computational neuroscience.
Contact Emer here:
Emer studied Physical Natural Sciences as an undergraduate at the University of Cambridge before moving to the University of York for an MSc in Cognitive Neuroscience. She is now a PhD student based at the MRC Cognition and Brain Sciences Unit in Cambridge, co-supervised by Tim Kietzmann (Donders) and Matt Lambon Ralph (Cambridge). She is interested in using artificial neural networks as a modelling framework for the human visual ventral stream in health and disease.
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Abdullahi completed his B.Sc. and M.Sc. in Artificial Intelligence specializing in neural computation. He is interested in the biophysical constraints and environmental pressures that drive organisation and information processing in the visual cortex. He aims to develop biologically-plausible recurrent neural network models that can solve visual problems in ecologically valid environments.