Uri Cohen
Blavatnik visiting fellow at the Computational and Biological Learning Lab, University of Cambridge
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Curriculum vitae
Contact email
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.