Pavel Izmailov

I’m a PhD student in Computer Science at NYU, working with Andrew Gordon Wilson. I am primarily interested in better understanding Deep Neural Networks and finding more efficient ways of training them. In particular my interests include loss surface analysis, optimization and regularization in deep learning. I am also excited about deep semi-supervised learning, Bayesian deep learning, generative models, Gassian processes and other topics.

In years 2017–2019 I was a PhD student in Operations Research and Information Engineering at Cornell University, after which I received an MSc degree and transferred to NYU. I received a BSc in applied math and computer science from the faculty of Computational Mathematics and Cybernetics of Lomonosov Moscow State University, where I was working in the Bayesian Methods Research Group under supervision of Dmitry Vetrov and Dmitry Kropotov.

In the summer of 2019 I completed a research internship at Amazon AWS in Palo Alto, working with Bernie Wang, Alex Smola. In the summer of 2020 I am excited to work with Matt Hoffman at Google AI in NYC!

I recently gave a talk on geometry of dnn loss surfaces at Broad Institute of MIT and Harvard together with Polina Kirichenko and Andrew Gordon Wilson.

You can contact me at pi390@nyu.edu and follow me on Twitter.

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Publications

Workshop Papers