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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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Voronoi-based Path Planning based on Visibility and Kill/Death Ratio Tactical Component

P. 129–140.
Makarov I., Pavel Polyakov, Roman Karpichev

We present an obstacle avoiding path planning method based on a Voronoi diagram adjusted with tactical component in a first-person shooter video game. We use a visibility measure to aggregate information on cover positions in offline and online game modes. In order to incorporate online learning based on frag map, we introduce a path finding algorithm minimizing the probability to walk along the path through dangerous zones, and on the contrary, choosing the best positions to shoot when observing a map level. Several implementations of collision free path finding are compared under efficiency, team goal achievements, and path length measures.

Language: English
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Keywords: path planningVoronoi DiagramNavigation MeshFrag MapTactical Path Finding
Publication based on the results of:
Applied network research with big data and new technological advances (2018)

In book

Supplementary Proceedings of the 7th International Conference on Analysis of Images, Social Networks and Texts (AIST-SUP 2018), Moscow, Russia, July 5-7, 2018
Aachen: CEUR Workshop Proceedings, 2018.
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