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July 20, 2026
Scientists Create Open Dataset for Studying Concentration
A team of Russian researchers, including scientists from HSE University–St Petersburg, has developed the first open multimodal dataset containing recordings of brain activity, heart function, and video observations to help researchers understand what happens in the human brain during deep concentration. In the future, the dataset could accelerate the development of neural interfaces, rehabilitation technologies, and AI systems. The article has been published in Scientific Data.
July 20, 2026
‘Science Is Universal-It Knows No Borders
Fuad Aleskerov, Tenured Professor and Director of the International Centre of Decision Choice and Analysis at HSE University, together with his colleagues, has developed methods of network analysis in bibliometrics that have made it possible to identify patterns in the appearance and citation of publications in academic journals, as well as their influence on each other. When one or a number of studies are frequently cited by a wide range of journals, this is an indicator that the research is of high quality. By contrast, extensive cross-citation within a limited group of journals increases the likelihood of identifying a network of predatory publications.
July 20, 2026
Scientists Propose Method for More Efficient Resource Use in Machine Learning
An international group of researchers, including mathematicians from the AI and Digital Science Institute at the HSE Faculty of Computer Science, has provided a theoretical justification for a simple and computationally efficient method of estimating uncertainty in Stochastic Gradient Descent (SGD). The paper has been published on the scientific preprint server arXiv.org and presented at AISTATS 2026.

 

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Изучение сетей коллабораций российских социологов: методологический подход и его апробация

Вестник Томского государственного университета. Философия. Социология. Политология. 2024. № 79. С. 221–232.
Maltseva D., Kim A., Shcheglova T.

Modern science research proceeds from the importance of studying social interaction between scientists to determine the effectiveness of research teams and form an idea of the structural changes necessary to increase their competitiveness. The community of Russian sociologists is characterized by weak integration into foreign sociological science and selective representation of researchers in the world scientific discourse due to the peculiarities of its formation, as well as disintegration at the local level due to the high level of centralization and inequality between the capital cities and regions in modern Russia. This study is aimed at studying collaborative networks in the scientific community of Russian sociologists in the period from 2010 to 2019. The main method of data analysis is the bibliometric network analysis of publications, which is a special case of applying the social network analysis methodology. The article presents a general methodological approach to the analysis of collaborative networks of Russian authors, which includes the formation of a bibliographic data base, the construction of collaborative networks, and a description of the network analysis strategy for studying collaboration in the community of Russian sociologists. The proposed approach is tested based on the analysis of data on the participation of Russian sociologists in conferences of the international sociological associations ESA and ISA in 2010–2019 and can be used for further analysis of publications of Russian sociologists. The results showed many unrelated groups of authors at the local level. At the same time, the links between the authors are well expressed at the level of organizations; there is a high level of geographical centralization and the dominance of three main institutions – the Russian Academy of Sciences, the National Research University Higher School of Economics and Saint Petersburg State University. This confirms the initial assumptions and actualizes the research questions of the study. The next step in the development of the methodology is the description of a workflow using specific tools and algorithms for collecting, processing, and analyzing data from Russian-language publications. In addition to the substantive interest, the scientific novelty and practical significance of the project lies in the development of an integrated methodological approach for the analysis of bibliographic data in Russian.

Research target: Sociology (including Demography and Anthropology
Language: Russian
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Keywords: сетевой анализсоциальная структураcollaborationnetwork analysisбиблиометрический анализсоциологическое сообществоbibliometric analysissociological community social structureколлаборация ученых
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