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News
September 11, 2026
How to Assess Students Knowledge in the Age of AI
A researcher at HSE University has proposed a flowchart to help lecturers decide how to assess students who use artificial intelligence. It shows where the use of AI should be restricted and where it can be incorporated into the learning process. The article has been published in IT Professional.
September 9, 2026
‘Balkan Hospitality Opens Doors: Studying Dialects on the Verge of Extinction
You cannot study spoken dialects from books. Instead, you need to go to a village, seek out its elders, and earn the trust of local residents before you can record hours of spontaneous stories. This is how Natalia Muravleva, Associate Professor at the Faculty of Humanities, conducts her research. Her internship in Serbia continued her long-standing study of dialects spoken by Macedonian settlers. In this interview, she discusses how diaspora cultural centres help researchers reach informants, why native speakers need to be interviewed only in their own language (otherwise, as she puts it, they may 'break'), and how a single field season helped her finalise her monograph. She also shares warm memories of autumn in Belgrade and of colleagues with whom grammar can be discussed in three languages at once.
September 9, 2026
Scientists Train Neural Network to Generate Process Plans from 3D Models
Researchers at the HSE FCS AI and Digital Science Institute have developed CAD2TechSpec, a framework that converts 3D models of mechanical parts into machining process plans—step-by-step instructions for machine tools. The solution aims to reduce the time required for the design and preparation of technical process documentation in mechanical engineering, aircraft manufacturing, and other high-tech industries. The study findings have been published in PeerJ Computer Science.

 

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Технологическое развитие и производительность труда: региональная проекция

Региональные исследования. 2024. № 1(83). С. 48–64.
Evseeva M., Стариков Е. Н.

Taking into account the current economic agenda, returning to a path of sustainable growth is a fundamentally relevant issue. One of the key drivers may be increased labor productivity. However, regional differences in the dynamics of scientific and technological potential may hinder the achievement of this goal. The article provides a comparative analysis of the dynamics of labor productivity and the models of technological development demonstrated by Russian regions for the period 2010–2020. To take into account regional heterogeneity, the country’s regions were grouped into four groups according to two dimensions – the level of labor productivity and the level of scientific and technological development. It was found that the growth of labor productivity in different groups of regions was accompanied by different combinations of capital-labor dynamics, changes in innovative and absorptive abilities, and production efficiency. The results of the study also indicate the priorities of regional scientific, technical and industrial policy: 1) support for the growth of capital-labor ratio in developed and developing regions; 2) for developing regions with high scientific and technical potential – priority areas of support should be related to increasing innovative capabilities, and for low ones – with stimulating increased production efficiency.

Research target: Economics and Management
Language: Russian
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DOI
Text on another site
Keywords: производительность трудаinnovationрегиональная экономикаregional economyтехнологическое развитиекапиталовооруженность labor productivity
Publication based on the results of:
Comprehensive scientific-methodological and information-analytical support for the development and implementation of state science, science and technology policy (2023)
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