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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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Networks under deep uncertainty concerning food security

The Journal of the New Economic Association. 2024. No. 3(64). P. 12–29.
Aleskerov F. T., Dutta S., Egorov D., Tkachev D.

We propose new models to find the vulnerable countries in terms of food security. These models are based on network analysis under deep uncertainty. The conditions of deep uncertainty affect the supply and demand of food, namely, carbohydrates of the countries. Under such conditions networks of the carbohydrate supply between countries are constructed. The countries vulnerability in terms of food security were studied by new centrality indices taking into account carbohydrate consumptions of countries and the possibility of group influence of countries to a country. Also, our models show direct and indirect dependence on import of carbohydrates from other countries. The scenario of one of such situations was constructed, and our models for studying this situation were tested. The vulnerable countries are identified in terms of carbohydrate consumption from main crops in different scenarios based on real data using our new models. The developed models can make the food policy of countries more efficient.

Research target: Economics and Management Mathematics
Language: English
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Keywords: продовольственная безопасностьсетевой анализсценарный анализnetwork analysisscenario analysisfood insecurityглубокая неопределенностьdeep uncertainty
Publication based on the results of:
Study of the models and methods of decision-making under conditions of deep uncertainty. Extension and testing of developed methods (2024)
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