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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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Почему девушки не выбирают STEM: гендерные различия в мотивационных ориентирах

Мониторинг общественного мнения: Экономические и социальные перемены. 2022. № 3. С. 115–135.
Лебедева Н. В., Vilkova K.

The rapid growth in the STEM (Science, Technology, Engineering, Mathematics) industry has demanded a considerable number of new employees, but women among them remain the minority. In this article, we examine gender differences in motivation in pursuing STEM degrees and careers. Our research follows a mixed-method sequential design and draws data from a student survey (n = 2 192) and semi-structured interviews with STEM students (n = 17). According to the results, men participate in STEM at higher rates than women, and motivation is related to student abilities and efforts they put in to succeed in STEM. Furthermore, we indicated gender differences among students in these aspects. Men are more confident in their abilities, arguing that they have a natural talent in STEM, and women, on the contrary, need to put more effort. However, in their opinion, numerous efforts often do not lead to success. As a result, women are more likely than men to think about changing their career paths after graduation from STEM. In turn, men tend to expect a high salary and rapid career growth. Understanding this motivation allows moving toward achieving gender balance in STEM

Research target: Education
Language: Russian
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DOI
Text on another site
Keywords: высшее образованиемотивациягендерmotivationgendergender segregationгендерная сегрегацияhigher educationSTEM EDUCATIONSTEM-образование
Publication based on the results of:
Educational environment and student experience in higher education (2022)
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