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September 4, 2026
Time to Showcase Your Research: Applications Are Now Open for Student Research Paper Competition 2026
Taking part in the Student Research Paper Competition (SRPC) gives you an opportunity to present your research to experts, receive an independent assessment, and determine the future direction of your work. The competition is open to students graduating in 2026 not only from HSE University but from universities in Russia and abroad. Papers may be submitted in Russian and English, and in some fields also in French, German, and Spanish.
September 4, 2026
‘Hedgehog Versus ‘Relatives: Researchers Measure How the Brain Responds to Unexpected Words During Natural Speech
Russian neurophysiologists, including researchers from HSE University, have demonstrated the feasibility of using event-related fields (ERFs) to study brain activity during natural speech perception. The researchers showed that this approach can be applied not only to individual words but also to continuous speech. Their findings indicate that words whose meanings differ significantly from the preceding context require longer processing times. The study also reveals that the brain processes function words in two stages: first, it identifies their grammatical role and then uses this information to predict the next word. The study has been published in Frontiers in Human Neuroscience.
August 25, 2026
Scientists Develop Algorithm for More Reliable Processors in Data Centres
Researchers from HSE MIEM and Samara University have developed the LRF-3D algorithm to automatically bypass idle nodes in three-dimensional networks-on-chip. Thanks to its hierarchical architecture, the algorithm outperforms existing solutions in both speed and path accuracy, improving processor reliability for use in data centres, supercomputers, and AI computing. The source code and test results are publicly available.

 

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Проектирование образовательных практик на основе многоагентного подхода

Искусственные общества. 2025. Т. 20. № 1.
Patarakin Y., Шишков М. С.

Modern educational systems are complex adaptive economic systems, and working with models of such systems allows students to better understand economic relationships and dependencies. In recent years, the framework of complex adaptive systems  has been actively used to analyze pedagogical situations. Through the prism of complex adaptive systems framework one can analyzeurban education systems, including a multitude of educational institutions interacting with each other and with the local community, where complex interactions between political decisions, funding, and educational outcomes are observed. This paper examines the transfer of skills in designing multi-agent models to the design of pedagogical practices. The study was carried out on the basis of Semantic MediaWiki, which made it possible to combine various programming environments (Snap!, NetLogo, StarLogo Nova, GAMA), models, datasets, and student works. A model of students choosing schools that differ in geographical location, tuition costs, student achievement levels, maximum capacity, and availability of public information is considered. 

Research target: Education Mathematics
Language: Russian
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Keywords: многоагентное моделированиеcomplex adaptive systemsсложные адаптивные системыNetLogoNetlogomultiagent systemSemantic MediaWikiSemantic MediaWikiStarLogo Nova
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