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News
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.
September 7, 2026
Biologists Discover 'Molecular Fingerprint' of Preeclampsia
Researchers at HSE University employed a new method to model hypoxia in placental cells during pregnancies complicated by preeclampsia and identified molecular markers of tissue hypoxia. Since hypoxia is one of the key mechanisms underlying preeclampsia, these findings are important for a more accurate and timely diagnosis of the disease and for the development of effective treatment methods. The paper has been published in Placenta.

 

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Технологии доверенного искусственного интеллекта

Информационные технологии. 2024. Т. 30. № 8. С. 400–410.
С.М. Авдошин, Е.Ю. Песоцкая, Патрушев К. А.

With the development of artificial intelligence (AI) systems, their popularity is growing. Such systems are used in many
areas, from customer analytics and search engines to voice assistants and medical research. The tasks assigned to the systems are becoming more and more complex, and therefore artificial intelligence often needs to operate on confidential data; the results of the system’s operation can have large-scale consequences. This creates a new problem: the problem of trusted artificial intelligence. The authors set the goal of systematizing knowledge about possible threats and vulnerabilities associated with the use of AI technologies, analyzing existing standards in this area, and also identifying and describing relevant technologies that can increase confidence in the use of intelligent systems.

Research target: Computer Science
Language: Russian
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DOI
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Keywords: машинное обучениедовериеtrustsecuritymachine learningигровой искусственный интеллектбезопасность artificial intelligence
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