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News
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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Актуальность, критерии и факторы кластерной региональной дифференциации студентов в рамках информатизации трансграничного образования

Вестник Российского университета дружбы народов. Серия: Информатизация образования. 2021. Т. 18. № 3. С. 272–283.
Fakova M.

Problem and goal. This article, based on the analysis of domestic and foreign experience, reveals the need to study the feasibility and possibility of dividing foreign students into regional clusters for the subsequent differentiation of methods and teaching materials within the framework of the development of approaches to the informatization of cross-border education. Methodology. A series of ascertaining experiments was carried out with students of the specialty “Economics” from Zambia, Mongolia, Kazakhstan, Uzbekistan and other countries, aimed at identifying differences in educational motivation, reflection and other characteristics of cross-border students. A model of approaches to informatization of cross-border education based on cluster differentiation is proposed. Results. A system of clusters was proposed, the expe-diency of introducing the described complex of criteria and factors, illustrated by the example of highlighting previous educational experience as one of the significant criteria for cluster regional differentiation of students, was substantiated. Conclusion. Students from different coun-tries have different motivation, experience and perception of information, in many respects this is facilitated by school education. There is a need to find a balance between co-operative and differentiated education of cross-border students. Cluster differentiation of cross-border students is advisable for the subsequent use of information technologies in the framework of ensuring the variability of methodological systems of teaching individual disciplines at a university.

Research target: Education Computer Science
Language: Russian
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Keywords: кластеринформационные технологииинформатизация образованияquality of educationcross-border educationтрансграничное образованиерегиональная дифференциацияinterregional differentiation information technologiesиндивидуализация образованияindividualization of educationtransnational education
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