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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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Тенденции развития научно-педагогических кадров в России

Экономика образования. 2014. № 1. С. 34–59.
Abankina I., Abankina T., Nikolayenko E., Filatova L.

The paper analyses current development trends of highly qualified and research and teaching personnel in the Russian economy, defines the problems that have been accumulated since the post-crisis period and the opportunities to solve them as regarding the measures taken by the Government to encourage the personnel reproduction. It evaluates some emerging positive developments concerning the support mechanisms applied to secure quality training of the highly qualified personnel, including within the research and educational structures of higher education establishments and research organisations. At the same time the development of human resources in research and education sectors needs to be backed by new mechanisms to support the reproduction of research and teaching personnel in order to achieve the objectives set in the public policy in this domain. The Russian economy requires a certain level of methodological and predictive analysis framework to estimate the needs for highly qualified personnel that should be responsive to the excepted outcomes and enable the mobility to respond to the external changes as well as to the in-house changes of research and educational establishments.

Research target: Education
Language: Russian
Full text
Text on another site
Keywords: научно-педагогические кадрыresearch and teaching staffthe potential of scientific and educational sectorstraining of highly qualified personnelreproduction of research and teaching staffпотенциал научной и научно-образовательной сферыподготовка кадров высшей квалификациивоспроизводство научных и научно-педагогических кадров
Publication based on the results of:
Changing Trends in Public Demand for Higher Education and the Economic Effects of Higher Education Re-structuring in Russia (2012)
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