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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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Стиль научного руководства как предиктор мотивации и выгорания аспирантов

Психологическая наука и образование. 2025. Т. 30. № 3. С. 100–110.
Marchuk L.

The research of the relationship between academic supervision styles and postgraduate students’ motivation, perseverance, well-being and burnout is presented. The study involved 142 PhD students (M=28.8, SD=5.2, 54% female). The theoretical basis of the work was self-determination theory, which allows us to understand the contribution of styles that support or frustrate basic psychological needs to the motivation and intrinsic outcomes of postgraduate students' research activities. The study used the Universal Perceived Locus of Causality (UPLOC), Academic Supervision Styles (QA2S), burnout scales, and well-being (The PERMA Profiler) questionnaire. The results showed that the factors of autonomous motivation are autonomous and structuring academic supervision styles, whereas the factors of external motivation and amotivation are controlling and chaotic academic supervision styles. The quality of motivation mediates the effect of academic supervision styles on PhD students’ perseverance and burnout. Autonomous and structuring styles are positively and chaotic and controlling styles negatively related to total and selected aspects of well-being. Autonomous and structuring styles are the most favourable for PhD students. Мastering them and getting rid of unfavourable styles (controlling and chaotic) can be targets of work when organising the professional development of academic supervisors.

Research target: Psychology
Language: Russian
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Keywords: мотивацияmotivationwell-beingнастойчивостьблагополучиебазовые психологические потребностиаспирантытеория самодетерминацииself-determination theoryperseveranceburnoutвыгораниеbasic psychological needsPhD studentsacademic supervision stylesстили научного руководства
Publication based on the results of:
Existential foundations of life well-being (2024)
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