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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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Scientific collaboration in Russian universities before and after the excellence initiative Project 5-100

Scientometrics. 2020. Vol. 124. No. 3. P. 2383–2407.
Matveeva N., Ferligoj A.

Changes in patterns of collaboration between Russian universities after the commencement
of the Russian university excellence initiative (Project 5-100) are studied in this paper.
While this project aimed to make leading Russian universities more globally competitive
and improve their research productivity, it also happened to increase their cooperation. An
analysis of affiliations and the co-authorship networks was conducted to explore scientific
collaborations between and within the participating universities. Such analysis facilitates
the investigation of the number of collaborations with other organizations, both domestic
and international cooperation, and disciplinary differences. By analyzing the co-authorship
networks, the position of universities in the academic network and the structure of collaborations
among the participants were examined. A sample of 30 Russian universities,
including participants in Project 5-100 and a control group of institutions with similar
characteristics, was used. After joining the project, the participating universities increased
both their cooperation with each other as well as with foreign universities and research
institutions of the Russian Academy of Sciences, especially in the high-quality segment. At
the same time, the collaboration patterns of non-participating universities did not change
significantly. The centrality of Project 5-100 universities in the global academic network
has increased, along with their visibility and coupling in the national network. The historical
division between university and academic sectors has diminished, while the participating
universities have started to play a more important role in knowledge production within
the country.

Research target: Economics and Management
Language: English
DOI
Text on another site
Keywords: social network analysisScientific collaborationBlockmodelinguniversity excellence initiativesCo-authorship networks
Publication based on the results of:
­­­ Analysis of incentives and preferences of economic agents in higher education, in the banking services and in public procurement (2020)
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