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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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Цифровая экономика: 2026 : краткий статистический сборник

M. : ISSEK HSE, 2026.
Abashkin V., Abdrakhmanova G., Vishnevskiy K., Gokhberg L., Demidkina O. V., Demyanova A., Zorina O., Kovaleva G. G., Korlyakova D., Kotsemir M. N., Kuzina L., Kuznetsova I. A., Ozerova O. K., Polyakova V., Popov E., Ratay T. V., Revyakin S., Rudnik P. B., Sakhno M., Skorokhodov N., Streltsova E., Fridlyanova S., Schugal N. B., Shcherbakov R., Iudin I., Bogdanov T., Bocharov M., Kovrigina M. V., Nechaeva E. G.
Under the general editorship: Anisimov N., С. С. Галкин, Gokhberg L., С. С. Карецкая, Kuzminov Y., А. В. Чукарин

This pocket data book contains the main indicators reflecting the relevance of digital technologies for enterprises and individuals, the activity of ICT sector enterprises, the infrastructure and personnel of the digital economy.

The data book includes information of the Russian Federal State Statistics Service (Rosstat), Ministry of Digital Development, Communications and Mass Media of the Russian Federation, European Statistical Office (Eurostat), Organisation for Economic Co-operation and Development (OECD), International Telecommunication Union (ITU), UNESCO, UN Department of Economic and Social Affairs, and results of methodological and analytical studies of the HSE Institute for Statistical Studies and Economics of Knowledge.

In some cases, the presented data specify those published earlier.

Research target: Mathematics Economics and Management
Language: Russian
Full text
DOI
Keywords: информационно-коммуникативные технологиицифровые технологииInformation Communication Technology (ICT)цифровая экономикаstatistics of the information societyсоциально-экономическая статистикаdigital technologies digital economy
Publication based on the results of:
National innovation system 2.0: involving key actors in transformation processes (2025)
Цифровая экономика: 2026 : краткий статистический сборник
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Existence and uniqueness results for strongly degenerate McKean-Vlasov equations with rough coefficients
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