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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.
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.
June 4, 2026
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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Lipid II as a Target for Novel Antibiotics:Structural and Molecular Dynamics Studies.

Russian Journal of Bioorganic Chemistry. 2018. Vol. 44. No. 6. P. 653–664.
Panina I. S., Chugunov A., Efremov R.

The growing problem of antibiotic resistance in medicine raises the attention to antimicrobial substances that act on non-protein molecules, which have more conservative structure comparing to proteins or peptides. One of the most promising and studied targets is lipid II — the participant of the bacterial cell wall biosynthetic pathway. Lipid II is present in the bacterial membrane only and has a conservative chemical structure. There are several classes of natural antibiotics acting on lipid II, some of which block the peptidoglycan synthesis by formation of a strong complex with lipid II, and others have an additional bactericidal mechanism involved a violation of the membrane integrity. This review examines the prospects for using such antibacterial substances as new drugs to combat antibiotic-resistant pathogens. The main emphasis is made on the studies of membrane-embedded lipid II structure and molecular mechanisms of its recognition by water-soluble antibiotics, and also on computer modelling of their interaction.

Research target: Biology Physics
Priority areas: IT and mathematics
Language: English
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DOI
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Keywords: молекулярная динамикабиомембраныantimicrobial peptidesintermolecular recognitionbiomembranescomputer simulation of macromolecules molecular dynamicsантимикробные пептидымежмолекулярное распознаваниекомпьютерное моделирование макромолекул
Publication based on the results of:
­­­Atomistic multiscale modeling of properties and processes in materials and living systems; analysis of efficiency of new supercomputer technologies (2018)
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