The Vysota Foundation announced the winners of the 2025 scholarship program

The V.P. Chichkanov Vysota Foundation for the Support of Young Scientists summed up the results of the 2025 scholarship program, the foundation's press service reported.

According to the results of the competitive selection, ten winners from various regions of Russia will receive a scholarship of up to 720 thousand rubles for the implementation of their own scientific projects. Eleven more finalists of the program will be able to benefit from mentoring, expert advice and the opportunity to launch pilot developments.

"Financial support is only part of the strategy. Our goal is to create conditions in which young scientists will not only thrive, but also contribute to maximizing their achievements, which will allow Russia to form a strategic scientific advantage. This is an investment in the long—term growth of the knowledge economy and technological sovereignty of Russia," said Roman Chichkanov, founder of the Vysota Foundation.

Among the fellows: Stanislav Tikhonov (Moscow State University, Kazan, researches the molecular mechanisms of aging and mortality in mammals), Ekaterina Moiseeva (Skoltech, Krasnoyarsk, works on exosome-based liquid cancer biopsy methods), Chiara Makievskaya (Moscow State University, Moscow, develops biocompatible implantable neural interfaces), Evgeny Sysoev (St. Petersburg State University, Moscow St. Petersburg, studies cellular stress and neurohormones that prevent cell death), Artur Zhemchuzhnikov (Kurchatov Institute, Moscow, creates a method for classifying schizophrenia according to fMRI data), Daniil Gorbunov (NES, Krasnoyarsk, studies the distribution of labor and capital in economies), Olesya Butrimova (NCFU, Stavropol, develops sustainable synbiotic and vitamin preparations), Anastasia Tsareva (NTU Sirius, Votkinsk, creates biodegradable medical materials), Yulia Tikhmeneva (DSTU, Rostov-on-Don, studies animal microbiota and antibiotic resistance using metagenomic analysis), Gleb Solovyov (Ufa, develops methods and algorithms for generative design of physical objects using deep learning models).

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