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June 5, 2026
Neural Network Maps as a Method for Constructing Mathematical Models
Scientists from HSE University–Nizhny Novgorod and the Institute of Physics Belgrade, Serbia, are jointly exploring the application of machine learning techniques and neural networks to the study of nonlinear dynamics. Natalya Stankevich, Leading Research Fellow at the Laboratory of Topological Methods in Dynamics of the Faculty of Informatics, Mathematics, and Computer Science at HSE University–Nizhny Novgorod, spoke to the HSE News Service about this international project.
June 5, 2026
‘In the Age of Technology, It Is Interesting to Look into the Past and Think about What We Can Take from It
Polina Tabakova decided to apply for a Philology degree at HSE in Nizhny Novgorod because she grew up in Mari El and did not want to move far away from the Russian forests. In an interview for the Young Scientists of HSE University project, she spoke about the genre of the campus novel, the existential drama of Kolobok, and a blackout version of Eugene Onegin.
June 5, 2026
HSE Scientists Develop Method to Compress Large Language Models Without Losing Quality
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science have developed a new compression method for large language models such as GPT and LLaMA that reduces their size by 25–36% without additional training or significant loss of accuracy. This is the first approach to use mathematical transformations—specifically, rotations of model weights—to make models more amenable to compression with structured matrices. The study results have been published in ACL Findings 2025. The code is available on GitHub.

 

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Analysis of Eye and Head Tracking Movements During a Puck-Hitting Task in Ice Hockey Players, Compared to Wrestlers and Controls

Psychology in Russia: State of the Art. 2024. Vol. 17. No. 3. Article 1.
I.S. Polikanova, Sabaev D., Bulaeva N. I., Panfilova E. A., Leonov S. V., Bugriy G. S., Bespalov B. I., Kruchinina A. P.

Background. The study of eye-movement strategies of athletes of various disciplines and skill levels is highly significant for sports psychology, since the results can be used in training to improve performance. Such studies are extremely scarce for ice hockey.

Objective. To determine successful eye-movement strategies for ice hockey players compared to wrestlers and controls (non-athletes) during puck-hitting tasks of various degrees of difficulty, using virtual reality.

Design. The study involved 31 participants (male), including 13 ice hockey players (age 20 ± 2.5), 9 wrestlers (age 19 ± 1.9), and 9 controls (age 19 ± 1.3). We used a pre-developed VR-PACE technology that simulates an ice rink in virtual reality (VR). The task was to hit pucks. VR was presented via the HTC Vive Pro Eye with a built-in eye tracker (100 Hz). We analyzed the parameter that reflected the share of puck presence in one of selected retina areas (0–5°, 5–10°, 10–15°, 15–25°, 25–35°) of the left and right eyes and the head.

Results. Ice hockey players exhibited longer puck-tracking using both the near periphery (5–15°) and central retinal area (0–5°). Puck speed had minimal impact on eye-movement strategies, and the visual focus on these areas remained consistent regardless of task type. For both wrestlers and controls, visual fixations in the central retinal area increased when tracking the puck without a motor response, likely leading to higher energy consumption and sensory fatigue.

Conclusion. The optimal eye-movement strategy involves parafoveal tracking in the near periphery (5–15°) and partial foveal tracking (0–5°), allowing for better object information retention and efficient puck trajectory tracking with reduced energy expenditure.

Research target: Psychology Mathematics
Language: English
DOI
Text on another site
Keywords: виртуальная реальностьдвижения глазeye movementseye trackingхоккейhockeyaйтрекинг (окулография) virtual realityайтрекинг в спортеeye-movement strategiesглазодвигательные стратегии
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