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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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Гендерные различия при выборе специальности в вузе в современной России

Мониторинг общественного мнения: Экономические и социальные перемены. 2017. № 3. С. 163–176.
Zamyatnina E.

Based on the full-time enrollment data in the Russian universities in 2011—2016, the paper provides an analysis of gender-related preferences among the applicants. Specialties where the share of the representatives of the same gender exceeded two-thirds on a regular basis are marked as «male» or «female». Those specialties where there is relative parity of men and women are referred to as «neutral». Almost all the male specialties are related to engineering; simultaneously, engineering sciences are not presented in the «neutral» and «female» groups.

An analysis of the Unified State Exam average score used by applicants to apply for the target program reveals that the results presented by female applicants are higher even if the program is «male». However, women having more choice opportunities this way do not use them to the full extent: only few male-dominated programs show a steady growth in the share of women. In such a situation, where the number of men enrolled in engineering programs significantly exceeds the number of women is typical not only for Russia but also for many EU countries. A series of studies points to the influence of popular gender stereotypes on the career choices of men and women as a major reason behind this phenomenon.

Research target: Sociology (including Demography and Anthropology
Priority areas: sociology
Language: Russian
Full text
DOI
Text on another site
Keywords: высшее образованиегендерgenderвыбор специальностиЕГЭhigher education
Publication based on the results of:
Monitoring the Quality of Enrollment in Russian Universities (2016)
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