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June 5, 2026
Neural Network Maps as a Method for Constructing Mathematical Models
Scientists from HSE University–Nizhny Novgorod and the Institute of Physics Belgrade, Serbia, are jointly exploring the application of machine learning techniques and neural networks to the study of nonlinear dynamics. Natalya Stankevich, Leading Research Fellow at the Laboratory of Topological Methods in Dynamics of the Faculty of Informatics, Mathematics, and Computer Science at HSE University–Nizhny Novgorod, spoke to the HSE News Service about this international project.
June 5, 2026
‘In the Age of Technology, It Is Interesting to Look into the Past and Think about What We Can Take from It
Polina Tabakova decided to apply for a Philology degree at HSE in Nizhny Novgorod because she grew up in Mari El and did not want to move far away from the Russian forests. In an interview for the Young Scientists of HSE University project, she spoke about the genre of the campus novel, the existential drama of Kolobok, and a blackout version of Eugene Onegin.
June 5, 2026
HSE Scientists Develop Method to Compress Large Language Models Without Losing Quality
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science have developed a new compression method for large language models such as GPT and LLaMA that reduces their size by 25–36% without additional training or significant loss of accuracy. This is the first approach to use mathematical transformations—specifically, rotations of model weights—to make models more amenable to compression with structured matrices. The study results have been published in ACL Findings 2025. The code is available on GitHub.

 

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Культуры вовлеченности в студенческое самоуправление в российских вузах: тусовщики, прагматики и граждане

Вопросы образования. 2024. № 4. С. 61–94.
Efimov D. B., Batischev A., Kostyuk A., Махсон А. М., Svoyski M.

The aim of this research is to explore the main models of student engagement in university self-government in Russia, to understand and categorize what drives the students’ participation in these institutions. The main content of the paper is based on a multi-stage coding and thematic analysis of 72 interviews conducted in the autumn of 2022 with student leaders of various Russian universities. The analysis results allow us to highlight three main student cultures of participation in representation bodies: the basic one is characterized by a predominant focus on personal socialization and individual development, the pragmatic one emphasizes the importance of financial and career incentives, while the civic one includes an orientation towards social recognition, helping others, and addressing public issues. The results provide valuable information for developing strategies to enhance the efficacy of working with different groups of students in Russian student representation, both at the institutional university level and at the regional or national level.

Research target: Education
Language: Russian
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Keywords: студенческое самоуправлениестуденческая вовлеченностьstudent representationstudent self-governmentстуденческое представительствоstudent engagementstudent councilsстуденческие советы
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