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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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The human resource dimension of science-based technology transfer: lessons from Russian RTOs and innovative enterprises

The Journal of Technology Transfer. 2018. Vol. 43. No. 2. P. 368–388.
Zaichenko S. A.

This study addresses ‘science-based’ technology transfer by research and technology organizations (RTO) whose mission is to combine intramural R&D and technology extension for industrial application. The paper is based on a unique database of Russian RTOs relating their science-based activity to technology transfer performance, on the one hand, and the contribution of R&D personnel sourced from universities to R&D output, on the other. The outcomes suggest a positive relationship between RTO scientific publication and technology transfer activity. Moreover, science-based outputs are contributed mostly by researchers coming to RTOs from academia. Such results are important to countries like Russia with many RTOs that play an important intermediary role between science and technological innovation. The study offers more fine-grained results regarding the differential impact of various types of academic personnel inflows in public versus private RTOs.

Research target: Mathematics Economics and Management
Priority areas: economics management
Language: English
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DOI
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Keywords: РоссияRussiainnovationтрансфер технологийинновация technology transferResearch and technology organizationsscience-based regimeR&D human resourcesRTOsнаучный режимчеловеческие ресурсы сферы исследований и разработокнаучно-технологические организации
Publication based on the results of:
Study of the activity of innovation process actors: development of the theoretical framework and methodological approaches (2018)
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