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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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Исследование корреляции характеристик деятельности преподавателя с удовлетворенностью дистанционным курсом иностранного языка

Педагогика и психология образования. 2023. № 1. С. 57–71.
Bogolepova S., Пивоварова А. А.

Now that universities compete for applicants, the quality of education and student satisfaction gain a particular significance. Instructors’ professional skills influence both parameters. This holds true for distance (online) teaching and learning, which has recently become a norm in higher education. This study aims to examine the correlation between student satisfaction with a foreign language distance course and instructor characteristics. The characteristics were singled out in the review of literature. The data were gathered through a survey among bachelor students who took a distance course of English for Specific Purposes. The analysis of correlations between professional characteristics of the instructors and the students’ satisfaction with the course demonstrated that professional skills and practices have a significant impact on student satisfaction with distance courses. In distance (online) learning, whether the instructor is able to motivate and engage students has the most significant correlation with student satisfaction. As for foreign language teaching, outlining course expectations, giving constructive feedback, managing class time, delivering the material in an accessible and vivid manner, providing opportunities for practice, bringing in variety and challenge ensure satisfaction, motivation and perceived usefulness of a course. Other crucial factors are whether the distance course is interesting and useful in the students’ perceptions, and the students’ levels of motivation. Instructors should be provided with necessary skills and instruments.

Research target: Education Philology and Linguistics
Language: Russian
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Keywords: дистанционное обучениеonline learningонлайн-обучениекомпетенции преподавателяcourse satisfactiondistance courseinstructor characteristicsteacher competenceхарактеристики деятельности преподавателяудовлетворенность учебным курсом
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