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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.
June 4, 2026
Machine Learning Models Can Help Reduce Volatility and Boost Stock Market Returns
The use of machine learning models makes it possible to achieve greater accuracy in predicting risks in the Russian stock market compared to classical econometric approaches. The predictive power of these models increases by 23%, while the average investor’s return can reach up to 13% per annum. These conclusions were drawn by Nikita Lysenok from the Department of Financial Market Infrastructure at the HSE Faculty of Economic Sciences. The paper has been published in Fundamental and Applied Mathematics.

 

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Баланс в условиях сверхзагруженности: структура и объемы рабочего времени преподавателей медицинских вузов

Кубанский научный медицинский вестник. 2026. Т. 33. № 2. С. 92–110.
Garmonova A., Shcheglova D., Камалова Г. Р., Opfer E., Гаврилов С. В.

Introduction. The study analyzes the structure and volume of workload for faculty at Russian medical universities amidst increasing student numbers, rising demands for students' clinical training, scientific output, and continuous professional education. The relevance of the topic stems from the contradiction between official regulatory requirements and the actual excessive workload of medical educators. The aim is to provide evidence-based illustration of the structure and volume of workload for medical university faculty within the regulatory framework of Russian higher education. Methods. Data from a large-scale questionnaire survey of 346 medical faculty members from three universities of different statuses were used, along with five expert interviews. A faculty typology is proposed: "clinical practitioners" (active patient care), "theorists" (analytical and laboratory work), and "non-clinical specialists and nursing". Data analysis methods included descriptive statistics, correlation analysis, and comparison (faculty from medical vs. non-medical universities). Results. Approximately 60% of faculty combine work at a medical university with clinical practice. The greatest workload is characteristic of "clinical practitioners": they are more involved in teaching at residency and postgraduate levels, lead continuing professional education (CPE) courses and electives, and have more additional jobs outside the university. Medical university faculty demonstrate lower indicators of research activity and academic mobility compared to colleagues from non-medical universities, predominantly publishing methodological works. High scientific performance is mainly demonstrated by top-academic staff (professors, heads of departments). The level of research activity (in terms of article count) is positively correlated with the number of additional external jobs and the number of subjects taught by a faculty member. About 10-15% of clinical faculty combine significant workload with high research performance, expert work, and classroom teaching of more than three subjects. The overload of medical educators may lead to risks of professional burnout and formalization in transmitting practical skills to students. Strategies for minimizing effort in publication activity are also attributed by the authors to the results of work "overload" combined with significant regulatory demands for work outcomes. Conclusion. The workload structure for medical educators is significantly more complex and voluminous than prescribed by official regulations. To reduce workload and increase efficiency, it is proposed to differentiate professional trajectories (methodologist, practitioner, researcher), simplify working conditions for practicing physicians, including through non-material incentives, reduce classroom teaching load, and enhance methodological and organizational support for research activities.

Research target: Education Social Sciences Medical and Health Sciences
Language: Russian
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DOI
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Keywords: учебная нагрузкавнерабочее времяклиническая практикапрофессиональное выгорание медицинских работниковclinical practiceTeaching loadfactors of professional burnout working hoursmedical university facultyпреподаватели медицинских вузов
Publication based on the results of:
Профессиональные стратегии преподавателей высшей школы в современной России (2025)
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