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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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HSE Global Cities Innovation Index: 2024

M. : ISSEK HSE, 2024.
Kutsenko E., Gokhberg L., Boos V., Boyakova K., Ivanova E., Ostashchenko T., Tyurchev K.
Leading author: Kutsenko E., Gokhberg L.
Under the general editorship: Gokhberg L., Kutsenko E.

HSE Global Cities Innovation Index (HSE GCII 2024) has been developed by the Russian Cluster Observatory of the National Research University Higher School of Economics Institute for Statistical Studies and Economics of Knowledge. It presents a measurement tool to evaluate the competitive edge of cities in terms of their attractiveness for the innovation economy leaders in technological development and creative industries.

The study covers over 1,000 agglomerations from 144 countries, where at least one of 27,925 leaders of the innovation economy is present – top enterprises (mega corporations, disruptive startups, and leading universities) and exceptional individuals (Nobel Prize laureates, highly cited researchers, popular designers, architects, artists, musicians, filmmakers, and developers).  The ranking is based on a unique system of 90 indicators calculated with the use of recognized international data sources (excluding expert estimates, surveys, and administrative data) that were grouped into three key blocks: Technological Development, Creative Industries, and Urban Environment. To affirm the reliability of the used data sources, a special statistical audit was conducted.

The report presents the ranking scores and examines key factors of attracting the world’s most successful representatives of the innovation economy to cities. It also discloses the ranking algorithm and provides detailed methodological comments. The publication includes 50 city profiles with the full information about their scores, benchmarking against the leader, and technological specializations.

The publication will be of practical interest to a wide range of readers, including technology entrepreneurs and researchers, artists and representatives of creative industries, urban governance practitioners, and professionals involved in the development of specific innovation economy sectors.

Research target: Economics and Management Political Science, International Relations, and Public Administration
Language: English
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DOI
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Keywords: innovationtechnologycreative industriescitiesurban environment
HSE Global Cities Innovation Index: 2024
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