Oksana Chernova

Oksana Chernova is a Research Fellow at the Technical University of Munich's Institute for Advanced Study (TUM-IAS), appointed in 2022 under the Fellowship for Ukrainian Scientists program. Hosted by the School of Computation, Information and Technology and mentored by Prof. Mathias Drton, she maintains her primary affiliation with Taras Shevchenko National University of Kyiv while conducting research at TUM.

Her work specializes in shape-constrained density estimation within nonparametric statistics, focusing on log-concave functions as infinite-dimensional generalizations of Gaussian densities. She addresses computational inefficiencies in higher-dimensional estimation through novel methodologies combining exponential series techniques with score matching procedures. This research enhances practical applications for data visualization, feature extraction, and tuning-parameter-free inference in modern statistical challenges.

As part of TUM-IAS's mission to foster interdisciplinary collaboration, Chernova contributes to advancing statistical theory applicable to real-world data analysis problems while representing the institute's support for displaced Ukrainian academics.