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July 24, 2026
'Physics Is What the World Is Literally Built On'
Physicist Nina Dzhanayeva, recipient of a Vladimir Potanin Foundation scholarship, focuses her research on nanophotonics. In this interview for the HSE Young Scientists project, she discusses nanowells, scientific intuition, and how physics can help in making frangipane cream puffs.
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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.

 

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AI in Vocational Training: A Qualitative Interview Study of Early-Stage Practitioners in the Real Estate Brokerage Industry in China

Educational studies. 2024. Vol. 1. No. 3. P. 180–200.
Wang F.

This study aims to unveil the individual and sectoral factors influencing the integration and utilization of artificial intelligence (AI) in vocational training among early-stage practitioners in China's real estate brokerage industry. The study involved in-depth interviews with 33 participants, each possessing less than two years of industry experience and demonstrating either experience with or a keen interest in AI applications. Rooted in the transformative potential of AI in vocational training, thematic analysis was employed to reveal the intricate interplay of individual factors—motivation, attitude, self-efficacy, and digital literacy—alongside sectoral elements such as policies, practices, and organizational culture. The findings illuminate the significant impact of these factors on the acceptance and utilization of AI, underscoring the complexity of participant attitudes, shaped by perceived usefulness and ease of use. Diverse levels of self-efficacy and digital literacy among participants regarding AI adoption were also evident. On the sectoral front, policies play a dual role, either providing support or imposing restrictions on AI adoption, while practices and organizational culture wield substantial influence over the opportunities and challenges associated with AI use. These empirical insights and best practices offer stakeholders valuable guidance to enhance employability and productivity in this ever-evolving industry. Importantly, this study advocates for a more inclusive approach in future research, addressing limitations in sample representativeness and recommending the integration of quantitative methodologies. This approach is crucial for fostering a comprehensive understanding of AI utilization in vocational training, ensuring robust insights for future advancements in the industry.

Research target: Economics and Management Education Social Sciences Computer Science
Language: English
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Keywords: человеческий капиталпрофессиональное обучениеискусственный интеллектVocational trainingразвитие талантовtalent developmentdigital hrmHuman capitalreal estate brokerageArtificial intelligence (AI)Цифровое HRMБрокерская деятельность в сфере недвижимости
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