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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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Особенности восприятия офлайн и онлайн учебного опыта студентами

Отечественная и зарубежная педагогика. 2025. Т. 1. № 6(109). С. 73–83.
Kuryan M., Voronina Y.

Relevance: The paper looks into how students perceive their learning experiences acquired in traditional in-person and online formats. The relevance of this research is substantial, given the context of digital transformation and personalization of higher education. The aim of the study is to analyse student characteristics - gender, year of study and educational profile - that may influence their preferences for either of the educational formats. Methods: The study, conducted in the form of a survey in 2024, involved undergraduate students at the HSE University in Nizhny Novgorod. The sample was stratified by gender, year of study, and academic major. The analysis focused on comparing parameters of learning experience, such as motivation, self-discipline, the social component of the learning environment, and students’ perceptions of course structure, materials, assignments, and assessment systems. Results: Female students rated socialization and interaction higher, especially in the offline format. Gender differences in the perception of student-teacher communication and course content were minimal, but women showed higher self-regulation. First-year students had the highest motivation. Economics majors were more positive towards both learning formats than their peers studying management and computer science. Conclusions: Students' preferences depend on many factors. The research results emphasize the need for individualized educational trajectories and flexible course design which take into account the characteristics of the learners.

Research target: Education Psychology
Language: Russian
DOI
Text on another site
Keywords: образовательная средаonline learningонлайн-обучениеlearning environmentstudents' characteristicsиндивидуализация образованияindividualization of educationoffline learningофлайн обучениеstudents' preferencesхарактеристики студентовпредпочтения студентов
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