Pavel Izmailov

photo of Pavel Izmailov

Contact:, Twitter

I'm a Research Scientist at OpenAI, working on AI alignment.

Starting in Fall 2024, I will be joining NYU as an Assistant Professor in the Tandon CSE department, and Courant CS department by courtesy.

In my research, I aim to build foundational understanding of models, training procedures, and their limitations. I use this understanding to develop practically impactful, interpretable, robust and broadly applicable methods and models. My interests include interpretability, large-scale models, out-of-distribution generalization, probabilistic deep learning, representation learning, and other topics.

In 2023, I defended my PhD in Computer Science at NYU, under the supervision of Andrew Gordon Wilson. 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 at 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 and Alex Smola. In the summer of 2020 I worked with Matt Hoffman at Google AI. Between June 2021 and February 2022 I worked with Alex Alemi and Ben Poole at Google as a research intern and a student researcher. In the summer of 2022 I worked with Lucas Beyer and Simon Kornblith at Google Brain.

Our work on Bayesian model selection was recently recognized with an Outstanding Paper Award 🏆 at ICML 2022!



Workshop Papers