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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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What semantic analysis can tell us about long term trends in the global STI policy agenda

The Journal of Technology Transfer. 2023. Vol. 48. P. 2249–2277.
Gokhberg L., Meissner D., Kuzminov I.

The scope, complexity and the “volume” of knowledge accumulated render producing an overview of the core themes of science, technology and innovation policies difficult. Reviews of this policy domain mostly either refer to general issues without deep immersion into details or focus on specific narrower aspects. The paper uses semantic analysis to identify major themes of science, technology and innovation policies over the last three decades and to trace their evolution towards current policy setting. We use semantic tools for processing and analysing documents produced by one of the major and highly reputable international expert bodies, the OECD Working Party on Technology and Innovation Policy. We show that selected themes remain in the mainstream even though being affected by regular policy adjustments and refinements and which disappear or appear with new challenges and expected solutions. Other themes appear niche or exotic themes which are under discussion for some time only.

Research target: Economics and Management
Language: English
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DOI
Text on another site
Keywords: science policysemantic analysisBig Data analysis text miningTechnology and innovation policiesEvidence based policyOECD Working Party on Technology and Innovation PolicyInternational policy agenda
Publication based on the results of:
The Future of Science: Megatrends Driven Transformation (2022)
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