Yandex School of Data Analysis

About

In recent decades, authors affiliated with Yandex School of Data Analysis have published 47 papers, which have received a total of 402 indexed citations. Scholars at this organization have produced 26 papers in Nuclear and High Energy Physics, 8 papers in Artificial Intelligence and 6 papers in Computer Networks and Communications on the topics of Particle physics theoretical and experimental studies (24 papers), Particle Detector Development and Performance (17 papers) and High-Energy Particle Collisions Research (7 papers). Their work is cited by papers focused on Molecular Biology (180 citations), Nuclear and High Energy Physics (126 citations) and Artificial Intelligence (57 citations). Authors at Yandex School of Data Analysis collaborate with scholars in Russia, United States and Switzerland and have published in prestigious journals including Nucleic Acids Research, Frontiers in Microbiology and Medicine. Some of Yandex School of Data Analysis's most productive authors include Ilya E. Vorontsov, Vsevolod J. Makeev, Ivan V. Kulakovskiy, A. Ustyuzhanin, Vladimir B. Bajić, Artem S. Kasianov, Yulia A. Medvedeva, Ulf Schaefer, F. Ratnikov and Evgeny Burnaev.

In The Last Decade

Fields of papers published by authors at Yandex School of Data Analysis

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers affiliated with Yandex School of Data Analysis at the time of their publication. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers affiliated with Yandex School of Data Analysis at the time of their publication.

Countries citing scholars working at Yandex School of Data Analysis

Since Specialization

Citations

This map shows the geographic impact of research produced by authors working at Yandex School of Data Analysis. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by papers produced at Yandex School of Data Analysis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yandex School of Data Analysis more than expected).

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar’s output or impact.

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