contact me at firstname.lastname@example.org
or on twitter
I am a PhD student at New York University Center for Data Science working with professor Andrew Gordon Wilson. I am also a Visiting Researcher at Meta AI (FAIR Labs) mentored by Mark Ibrahim, as a part of the FAIR-NYU AI Mentorship program. I am working on deep learning robustness to distribution shift and out-of-distribution generalization. I am also broadly interested in probabilistic deep learning learning, uncertainty estimation and generative models.
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. During my undergrad, I worked at Bayesian Methods research group with professor Dmitry Vetrov.
In summer 2022, I interned at Meta AI with Hamed Firooz, Randall Balestriero and Ramakrishna Vedantam and worked on biases of data augmentations. In summer 2021, I interned at Cold Spring Harbor Laboratory with Tony Zador and worked on meta-learning and neuroscience applications. In summer 2020, I interned at DeepMind with Mehrdad Farajtabar, Razvan Pascanu and Balaji Lakshminarayanan, and worked on task-agnostic continual learning. 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.