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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.
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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.
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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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Gender Inequality in Data Science and Artificial Intelligence: Labor Market Analysis

Ch. 5. P. 103–130.
Serova E., Frolova M.

The importance and role of modern technologies and Artificial Intelligence (AI)
cannot be overestimated. AI and Data Science are developing rapidly and issues of
gender inequality in this area are becoming of paramount importance. This paper
is devoted to the analysis of gender inequality in AI and Data Science in Russia.
The study examines differences in the expected wages between men and women,
as well as their skills and educational levels, based on data from the HeadHunter
platform. The results show that women have the same skills as men. However, by
using linear regression, we reveal that there is a significant gender gap in expected
salaries, indicating that women systematically underestimate their professional
qualities compared to men. In the study, we first examine and analyze research,
then formulate a theoretical framework. Based on the theoretical framework, we
formulate hypotheses and justify the methodology. Afterwards we describe the stages
and results of the analysis.

Language: English
Full text
DOI
Text on another site
Keywords: labour marketeducationRussiaprofessional skillsgender inequalityData Science gender gapArtificial intelligence (AI)expected salary

In book

Critical Aspects in Advanced Human Resource Management
Critical Aspects in Advanced Human Resource Management
IGI Global Scientific Publishing, 2025.
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