I am a Senior Data Scientist at Walmart Global Tech (AdTech team). I recently earned my PhD from the joint program between Statistics & Data Science and Machine Learning departments at Carnegie Mellon University, where I had been fortunate to be advised by Professor Aaditya Ramdas. Prior to joining CMU, I obtained my BSc and MSc degrees at Moscow Institute of Physics and Technology and Skoltech.

My most recent research interests include predictive post-hoc uncertainty quantification (including conformal prediction and calibration) and anytime-valid inference (such as sequential nonparametric two-sample and independence testing). I am also interested in designing practical methods for statistical inference in presence of distribution shifts.

Interests

- Sequential testing and safe, anytime-valid inference
- Distribution-free uncertainty quantification (conformal prediction, calibration)
- Distribution shifts

Education

PhD in Statistics & Machine Learning, 2023

Carnegie Mellon University

MSc in Applied Mathematics & Computer Science, 2018

Skolkovo Institute of Science and Technology, Moscow Institute of Physics and Technology

BSc in Applied Mathematics & Physics, 2016

Moscow Institute of Physics and Technology

- alexpodkopaev94 AT gmail DOT com