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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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Советы директоров российских компаний в контексте ESG-трансформации

Вопросы экономики. 2024. № 10. С. 42–76.
Ivashkovskaya I., Makeeva E. Y., Popov K.

Achievement of the UN Sustainable Development Goals at global and national levels is possible only in case of successful implementation of ESG principles in corporate strategies, meaning development of corporate environmental responsibility, social responsibility, high quality and transparency of corporate governance. Characteristics of board of directors as a superior corporate governance body are among the key determinants of corporate ESG transformation. This research includes comparative analysis of board composition and human capital characteristics in the largest Russian public non-financial companies, qualified as “leaders” and “outsiders” in terms of ESG transformation basing on corporate ESG rankings by RAEX Europe. According to obtained results, companies with higher ESG rankings are characterized by higher level of board’s independence and national diversity. Moreover, higher presence of independent directors with academic degrees and diversified educational majors in “leading” companies is proved. Finally, significant difference in board members’ professional experience is identified for companies from different ESG ranking clusters. These results not only broaden an evidence on board role inц corporate ESG transformation, but also are relevant in the context of considerable changes of corporate governance composition in large Russian companies in 2022 and 2023 years.

Research target: Economics and Management
Language: Russian
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Keywords: корпоративное управлениечеловеческий капиталсовет директоровcorporate governanceустойчивое развитиеstakeholder theoryboard of directorsagency theoryагентская теорияhuman capitalsustainable developmentESGESGresource-based theoryресурсная теориястейкхолдерская теория
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