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News
May 25, 2026
HSE Scientists Train Neural Network to 'Hear' Faults in Electric Motors
Researchers at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a new method—the Signature-Guided Data Augmentation (SGDA) framework—that achieves 99% accuracy in motor fault detection and 86% accuracy in fault classification. The application of this approach can reduce industrial equipment repair costs, minimise downtime, and improve production safety. The study results have been published in Engineering Applications of Artificial Intelligence.
May 25, 2026
'The Humanities Serve as a Conscience'
Maria Mizernaia studies Soviet literature and the history of book publishing. In this interview for the HSE Young Scientists project, she discusses plans to publish a novel about besieged Leningrad, AI-provoked reflections on what it means to be human, and how novels can help satisfy our dopamine hunger.
May 25, 2026
Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
Is it possible to predict, based on the configuration of streets and buildings, where a café will open or where traffic congestion will occur? Participants in the Spatial Analysis and Modelling of Urban Processes research and study group use open data and machine learning to identify universal patterns. Alexander Sheludkov and Eduard Somov discuss the purpose of comparing cities, the need for new forms of urban statistics, and how open data is transforming approaches to urban studies.

 

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Преподаватели российских вузов в условиях пандемийной цифровизации: между автономией и контролем

Мониторинг общественного мнения: Экономические и социальные перемены. 2021. № 3. С. 134–154.
Abramov R., Gruzdev I., Zakharova U., Terentev E.

Digitalization of higher education and the accompanying academic and expert discussions began long before the COVID‑19 pandemic. However, the forced transition to remote learning at Russian universities in 2020 actualized a new round of debates on how the use of digital technologies is changing the landscape of higher education, the roles and modes of work of academic professionals. This paper is based on a series of semi‑structured interviews with the teaching staff of 37 Russian universities, which were collected in March‑June 2020. Interviews were aimed at the complex analysis of the teaching profession transformations in the conditions of remote force majeure. The key attention is paid to the transformations of academic autonomy in the new conditions. We show that in the conditions of "forced remote teaching", two multidirectional trends are observed. On the one hand, in the context of an unprecedented natural experiment on the mass transfer of all work processes to a remote format, there is a revival of traditional forms of academic autonomy through the self‑organization of the teaching community, the emergence of networks of cooperation and mutual support between academic professionals. On the other hand, teachers note the strengthening of administrative control and bureaucratization of the educational process. In some cases, this leads to an escalation of the conflict between the administration and the teaching community and is perceived by the latter as a threat to academic autonomy. The presented analysis concludes with a discussion of possible measures that can be taken to reduce the potential negative effects of the identified trends on the entire higher education system.

Research target: Economics and Management Sociology (including Demography and Anthropology Education
Priority areas: sociology management
Language: Russian
DOI
Text on another site
Keywords: высшее образованиеакадемическая профессияакадемическая автономияacademic autonomyacademic professionцифровизацияhigher educationdigitalizationреформы высшего образования и наукиCOVID-19 pandemicпандемия COVID-19reforms of higher education and scienceuniversity teachersуниверситетские преподаватели
Publication based on the results of:
Цифровая трансформация образовательной системы: изучение инновационного потенциала, распространения инноваций на микро, мезо и макроуровнях и разработка механизмов сопровождения реформ (2019)
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