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News
June 2, 2026
Discovering Science through Russian Language: HSE Prep Year Students Present at International Conference in Kazan
On May 23, 2026, the V International Scientific and Practical Conference ‘Discovering the World of Science’ took place in Kazan at the Preparatory Faculty for International Students of Kazan Federal University. Four students of the HSE International Preparatory Year took part in the event: two delivered their presentations in person, while two participated online. Their work was supervised by Acting Director of the International Prep Year Irina Isaeva and lecturer Ekaterina Kozhemyakova.
May 25, 2026
HSE Scientists Train Neural Network to 'Hear' Faults in Electric Motors
Researchers at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a new method—the Signature-Guided Data Augmentation (SGDA) framework—that achieves 99% accuracy in motor fault detection and 86% accuracy in fault classification. The application of this approach can reduce industrial equipment repair costs, minimise downtime, and improve production safety. The study results have been published in Engineering Applications of Artificial Intelligence.
May 25, 2026
'The Humanities Serve as a Conscience'
Maria Mizernaia studies Soviet literature and the history of book publishing. In this interview for the HSE Young Scientists project, she discusses plans to publish a novel about besieged Leningrad, AI-provoked reflections on what it means to be human, and how novels can help satisfy our dopamine hunger.

 

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Прогноз результатов олимпиады-2014 в мужском одиночном фигур-ном катании методами искусственного интеллекта

Современные проблемы науки и образования. 2014. № 1.
Yasnitsky L., Внукова О. В., Черепанов Ф. М.

A computer program is designed to predict outcomes in men´s singles figure skating in 2014. Program is based on a neural network trained on the results of the previous world championships. There is a demonstration prototype, which assesses the chances of winning for each of the four possible candidates. The program also allows to evalu-ate the influence of the athlete parameters for their athletic successes, as well as to select the optimal combination of these parameters for each athlete. By examining of the developed mathematical model were derived recom-mendations for the main contenders for victory: E. Plushenko, P. Chan, D. Weier, R. Kevin, to improve their ath-letic performance.

Research target: Mathematics Computer Science
Priority areas: IT and mathematics
Language: Russian
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Keywords: искусственный интеллектнейронная сетьforecastartificial intelligenceчемпионат
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