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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.
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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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Machine Learning Models Can Help Reduce Volatility and Boost Stock Market Returns
The use of machine learning models makes it possible to achieve greater accuracy in predicting risks in the Russian stock market compared to classical econometric approaches. The predictive power of these models increases by 23%, while the average investor’s return can reach up to 13% per annum. These conclusions were drawn by Nikita Lysenok from the Department of Financial Market Infrastructure at the HSE Faculty of Economic Sciences. The paper has been published in Fundamental and Applied Mathematics.

 

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Вычисление и особенности использования коэффициента теплоотдачи в CAE программах расчета теплового режима

Электрооборудование: эксплуатация и ремонт. 2026. № 2. С. 75–85.
Manohin A.

An extended method for calculating heat transfer coefficients using programs
for automated analysis of the thermal regime of TRIANA (ASONIKA-T) radio-electronic
equipment for various designs is proposed. Based on the analysis of the obtained
heat transfer coefficients, it is shown how to set realistic values for the convective
heat transfer coefficient in SOLIDWORKS Simulation and other CAE thermal analysis
systems. The possibilities of using the total heat transfer coefficient, taking into account
convection and radiation, to speed up calculations without compromising the accuracy
of the results are demonstrated.

Research target: Engineering and Technology Electronics and Electrical Engineering
Language: Russian
Full text
Text on another site
Keywords: тепловой режимАсоника-ТCAE-системаПК ТРиАНАASONIKAheat dissipationвычислительное моделированиеthermal regimeTRIANASOLIDWORKS SimulationтеплоотдачаSOLIDWORKS Simulation
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