Hey there! I’m a 5th year PhD student in the joint program between Statistics & Data Science and Machine Learning departments at Carnegie Mellon University. I’m fortunate to be advised by Professor Aaditya Ramdas. We focus on topics related to building reliable ML systems: distribution-free uncertainty quantification (conformal prediction, calibration), detecting and handling distribution drifts. Recently, I have also been looking into topics related to safe, anytime-valid inference (valid inference after peeking at observed data). Before joining CMU, I obtained BSc and MSc degrees at Moscow Institute of Physics and Technology and Skoltech.
(!!!) I am actively seeking for industry research positions with start date in Summer–Fall, 2023.
PhD in Statistics and Machine Learning, in progress
Carnegie Mellon University
MSc in Applied Mathematics, 2018
Skolkovo Institute of Science and Technology, Moscow Institute of Physics and Technology
BSc in Applied Mathematics, 2016
Moscow Institute of Physics and Technology