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August 25, 2026
Scientists Develop Algorithm for More Reliable Processors in Data Centres
Researchers from HSE MIEM and Samara University have developed the LRF-3D algorithm to automatically bypass idle nodes in three-dimensional networks-on-chip. Thanks to its hierarchical architecture, the algorithm outperforms existing solutions in both speed and path accuracy, improving processor reliability for use in data centres, supercomputers, and AI computing. The source code and test results are publicly available.
August 24, 2026
Researchers Develop Method for Direct Generation of Regulatory DNA
Researchers at HSE University have developed a model for generating promoters and enhancers—DNA sequences that regulate gene activity. The model works directly with DNA nucleotides, without first transforming them into a continuous numerical representation. This solution could be useful for applications in synthetic biology and gene therapy. The study results were presented at the ICLR 2026 Workshop ‘Generative AI in Genomics (Gen^2): Barriers and Frontiers.’
August 21, 2026
Social Integration: At the Crossroads of Knowledge and Values
The International Laboratory for Social Integration Research (ILSIR) at HSE University studies the challenges faced by vulnerable groups and explores ways to help them participate fully in everyday life. To develop effective solutions, the laboratory’s researchers combine cutting-edge methods with practical fieldwork. In this interview with the HSE News Service, Laboratory Head Elena Iarskaia-Smirnova discusses the laboratory’s work.

 

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Роль высшего учебного заведения в пространственной поляризации молодежи

Экономика региона. 2019. Т. 5. № 4. С. 1103–1114.
Gabdrakhmanov N., Никифорова Н. Ю.

The expansion of applicants’ opportunities for choosing a university, unfortunately, did not completely eliminate the spatial factor in the process of selecting an educational institution. The majority of students are still graduates of local schools. The conducted analysis allows considering university as an element of the implementation of the strategic goal aimed at preserving and attracting human resources, as well as accumulating human capital. Thereby, it confirms that universities play an important role in the region’s socio-economic development by preserving and attracting youth of youth. For analysing the demographic consequences of the spatial polarization of youth we used the Lexis grid. The curve of the dynamics of the number of cohorts, built on the basis of the grid, revealed the most mobile group among the population aged from 17 to 19. The analysis of the existing Russian and foreign approaches to assessing the university’s role in regional development made possible making an analogy with the law of universal gravitation concerning this study. We proposed a gravity model and tested it at Kazan Federal
University, one of ten federal Russian universities. The results of the study allowed assessing the spatial effect of the university on the polarization of youth. In this study, we hypothesised that there is a neighbourhood effect in higher education, namely an educational migration between neighbouring regions with different levels of socio-economic development. We tested this hypothesis in the geographical framework of the Volga Federal District using the official statistics and admission data of Kazan Federal University. The constructed gravity model of the university allowed assessing the scale and strength of this influence on attracting applicants from neighbouring subjects. Moreover, it allowed determining the regions of potential growth of influence. Such regions include the Republic of Chuvashia, the Orenburg Region and the Republic of Bashkortostan due to demographic conditions, logistics and the positioning of Kazan Federal University in the Volga Federal District.

Priority areas: economics management state and public administration
Language: Russian
Full text
DOI
Keywords: высшее образованиеПриволжский федеральный округобразовательная миграцияаттракторгравитационная модель миграцииVolga Federal districteducational trajectoryneighborhood effectshigher education gravity modeleducational migrationсоседствоРеспублика Татарстанterritorial accessibility Republic of TatarstanКазанский федеральный университетсетка ЛексисаKazan federal universityLexis diagram
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