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June 2, 2026
HSE Study Reveals Imbalance in the Generative AI Market
Researchers at HSE University analysed how effectively the global generative artificial intelligence market converts investment into real revenue, concluding that AI is currently developing faster than it is paying off. The results have been published in the journal Foresight and STI Governance.
June 2, 2026
Discovering Science through Russian Language: HSE Prep Year Students Present at International Conference in Kazan
On May 23, 2026, the V International Scientific and Practical Conference ‘Discovering the World of Science’ took place in Kazan at the Preparatory Faculty for International Students of Kazan Federal University. Four students of the HSE International Preparatory Year took part in the event: two delivered their presentations in person, while two participated online. Their work was supervised by Acting Director of the International Prep Year Irina Isaeva and lecturer Ekaterina Kozhemyakova.
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.

 

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Шоковая инновация: концептуализация процесса цифровой трансформации образования в период пандемии

Образование и саморазвитие. 2023. Т. 18. № 2. С. 100–117.
Диана О. Королева, Анастасия А. Андреева, Татьяна Е. Хавенсон

The article considers the transition to distance learning in the context of COVID-19 pandemic as innovation. In particular, it shows that the spread of innovation in an extremely fast and compressed way does not fit the classical model of innovation diffusion by E. Rogers. Based on the results of the analysis, the authors supply the innovation theory with a model of shock innovation which aims to describe the phenomenon of momentary transformations. For that reason a comprehensive and extensive description of innovation diffusion was narrowed down to three key characteristics and linked to three levels (micro-, meso- and macro-). Narratives of principals which have been extracted from the interviews (N=10) were compared with the characteristics of this three-levels model. The analysis revealed that shock innovation a shock innovation is characterized by the fact that (1) the initial impulse has a source, external to the system, (2) requiring an obligatory response (forced change); (3) manifested by an innovative “breakthrough” due to the extreme mobilization of the resources; and (4) “densification” of traditional innovative processes for the diffusion of innovation at three levels - individual (micro), group (meso-) and systemic (macro-). The discussion highlights the aspects of the identified characteristics that should be taken into account in designing the strategies of schools’ development as well as filling the deficiencies of the educational system generated by the pandemic.

Research target: Education Sociology (including Demography and Anthropology
Language: Russian
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Keywords: innovationдистанционное обучениеинновацияdistance learningdiffusion of innovationsцифровизация образованияdigitalization in educationconceptual framework of COVID-19 in educationтеория диффузии инновацийконцептуализация процессов пандемии
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