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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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Peaks, Slopes, Canyons and Plateaus: Identifying Technology Trends Throughout the Life Cycle

International Journal of Innovation and Technology Management. 2017. No. 14.
Efimenko I., Khoroshevsky V. F.

A novel domain-independent approach to technology trend monitoring is presented in the paper. It is based on the ontology of a technology trend, hype cycles methodology, and semantic indicators which provide evidence of a maturity level of a technology. This approach forms the basis for implementation of text-mining software tools. Algorithms behind these tools allow users to escape from getting too general or garbage results which make it impossible to identify promising technologies at early stages (early detection, weak signals). Besides, these algorithms provide high-quality results in extraction of complex multiword terms which correspond to technological concepts forming a trend. Methodology and software developed as a result of this study are applicable to various industries with minor adjustments and require no deep expert knowledge from a user.

Priority areas: humanitarian
Language: English
Keywords: weak signalsTechnology trend monitoringEmerging Trends
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