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Subject
News
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.
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.

 

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Искусственный интеллект в китайской журналистике: спектр применения, оценка эффективности и профессиональные риски

Мир науки, культуры, образования. 2025. № 5. С. 408–412.
Проскурнова Е. Л., Чэнь Н., Алгави Л. О.

The article examines the ways in which technology is used by journalists in China. The purpose of the study is to identify algorithms for working with artificial intelligence and identify specific AI programs and individual functions that contribute to the creation of journalistic materials, as well as to determine the attitude of editorial staff of the Chinese media to various aspects of the development of machine learning programs. The study is based on a standardized questionnaire compiled by the authors and filled out by 2,500 respondents. The collected answers allowed us to determine how often journalists resort to AI, what worries they associate with them, what kind of options they consider insufficiently effective, and whether they believe in the reality of gradually replacing people with machines in the media system.

Research target: Media and Communications
Language: Russian
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Keywords: журналистикаКитаймедиа искусственный интеллект
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