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 and follow me on Twitter.



Workshop Papers