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News
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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Современный мировой ландшафт онлайн-обучения наукам о данных

Высшее образование в России. 2022. Т. 31. № 4. С. 129–147.
Никольский В. С., Лукашенко М. А., Шарова Е. А.

 

Data science as an emerging branch of applied knowledge and a new field of study
is showing a strong momentum. Besides, the corresponding sphere of educational research is
actively developing. At the same time, most of the scientific publications are aimed at studying
specific issues related to the content of the programs and their methodological support. The
wider context and especially the international perspective are lacking for the necessary atten-
tion of researchers.
In this regard, the purpose of our study was to summarize and systematize information about
training programs in the field of data science presented on online platforms of the main macro-re-
gions – America, Europe and Asia. For this purpose, we found out what elements the corpus of data
science training programs consists of, as well as how courses are distributed on educational plat-
forms by countries, organizational providers, level of education and duration of study. Based on the
data obtained, we conducted a comparative interregional study of educational programs presented
on online platforms.
The findings made it possible to draw conclusions about the specifics of the global landscape of
data science online education, as well as to determine the specifics of the Russian segment and to
formulate recommendations for solving significant problems of the domestic economy using data
science online education

Research target: Education
Language: Russian
Full text
DOI
Text on another site
Keywords: обучениеlearningbig dataнауки о данныхМООК data sciencedigital online platforms MOOCs онлайн-платформы большие данные
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