Uri Cohen

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Blavatnik visiting fellow at the Computational and Biological Learning Lab, University of Cambridge

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Blavatnik Cambridge Fellowships

About me

I am an aspiring scientist in the field of computational neuroscience, interested in developing theories on the dynamics of learning and memory in the brain, with possible applications to machine learning. I have strong mathematical background and hands-on experience with advanced methods from statistical physics and computer science, applied to analyze problems and experimental results from neuroscience and machine learning.

PhD Thesis

Title: Analysis of invariant object representations through linear classification of manifolds.

Advisor: Prof. Haim Sompolinsky

In my PhD thesis, I used statistical physics methods to analyze neuronal responses to objects and measure the properties important for linear object classification. Those are geometric properties of object manifolds which I use to shed light on object representations in artificial deep networks and in the brain and how it changes across levels of processing.

Research Interests