I am a PhD student at New York University Center for Data Science, working with professor Andrew Gordon Wilson. I am broadly interested in probabilistic deep learning, distribution shift, uncertainty estimation and generative models. Outside of my primary research interests, I am excited about neuroscience and computational biology. In summer 2021, I am interning at Cold Spring Harbor Laboratory with Tony Zador and working on meta-learning and neuroscience applications.
Before joining NYU, I was a PhD student in Operations Research and Information Engineering at Cornell University. I received a BS in Computer Science at Higher School of Economics in Moscow. During my undergrad, I worked at Bayesian Methods research group with professor Dmitry Vetrov.
In summer 2020, I interned at DeepMind with Mehrdad Farajtabar, Razvan Pascanu and Balaji Lakshminarayanan, and worked on task-agnostic in continual learning. In 2019-2020, I was also supported by DeepMind fellowship. In summer 2018, I interned at Machine Learning and Optimization Lab at EPFL and worked with professors Martin Jaggi and Dan Alistarh on low-precision training of neural networks. I also spent two summers (2016, 2017) at Google as a Software Engineering intern.