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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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Russian Scholarly Journals in Science Communication

Higher Education in Russia and Beyond. 2017. Vol. 1. No. 11. P. 7–9.
Dyachenko E., Fursov K.
The paper summarises results of a pilot study aimed at assessment of the representation of Russian science in the media in order to understand to what extent contemporary Russian academic journals are included into popular science communication. The analysis showed that most of the media publications reporting on the achievements of Russian scientists did not cite academic publications. Low visibility of Russian scholarly journals in popular media calls into question the importance of their role in science communication. The probable reason for that in the Russian academia, “the weight” of a statement depends more on the social status of a scientist or other public figure than on the system of scientific communication through professional journals.  

 

 

Research target: Sociology (including Demography and Anthropology Mathematics
Priority areas: sociology
Language: English
Keywords: Russiaacademic journalsscience communicationmedia visibility
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