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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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Связь результатов Единого государственного экзамена и успеваемости в вузе

Вопросы образования. 2014. № 1. С. 176–199.
Khavenson T., Soloveva A. A.

This paper analyzes the possibility of predicting efficiency of learning in a higher education institution based on results of the Unified State Exam (USE). In particular, the authors test the hypothesis that USE results in different subjects are equally efficient predictors of further student performance. Methods of regression analysis have been used to assess how preliminary examinations (both total USE points and points in specific subjects) affect academic performance in higher education. The research involved about 19,000 students enrolled at five Russian higher education institutions between 2009 and 2011. As long as the sample included institutions of different profiles, individual regressions were calculated for each faculty. A meta-analysis of regression coefficients was performed later to bring the data together. Average firstyear grade was used as the key university performance factor. It was found out that USE points were only related to performance in the second and the subsequent years through performance in the first year, i. e. indirectly. The research results allow to conclude that predictive capacity of total USE points is high enough to accept this examination as a valid student selection tool. The explained variation in university performance varies from 15 to 35% in different faculties. Predictive capacity of particular subjects making the USE total points is relatively the same, but USE points in mathematics and Russian are often the best predictors of performance. The paper also analyzes the relation between USE points and another student selection tool — results of academic competitions in specific subjects

Research target: Education
Language: Russian
Full text
Keywords: Единый государственный экзамен (ЕГЭ)олимпиады школьниковвступительные экзаменыentrance examinationRussian Unified State Exammeta-analysisмета-анализПрогностическая валидностьpredictive validityhigh school academic competitionsperformance in higher education institutionуспеваемость в ВУЗе
Publication based on the results of:
Detailed Analysis of the Results of Education Quality Research in the Context of Economic Indicators in Education (2013)
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