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News
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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Business Architecture Flexibility as a Result of Knowledge-Intensive Process Management

Global Journal of Flexible Systems Management . 2017. Vol. 18. No. 1. P. 73–86.
Gromoff A., Bilinkis (Stavenko) J., Kazantsev N.

In 2016 a survey was conducted among Russian companies to discover the most common problems associated with flexibility of business process management. A gap between strict process formalization demands and unpredictable nature of many knowledge-intensive operations was identified. The article suggests an approach to facilitate process management via combined context-aware set of methods. Firstly, the key terms are selected to serve as special cause indicators of variation in a process instance based on risk profiles. Afterward a cloud service is called, which automatically analyzes semantic annotation of the concrete process instance. Risk detection service identifies potential operational risks and in case of unexpected process execution complexities notifies users. Finally, expert search service calls for an expert in an organization automatically to create expert community. This novel approach could be used for knowledge-intensive business sectors (such as Research and Development) or in any organization interested in increasing its agility in changing business environment.

Research target: Computer Science Economics and Management
Priority areas: business informatics
Language: English
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DOI
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Keywords: business process management (BPM)business architectureBusiness flexibilitybusiness agilityKnowledge-intensive industriesKnowledge-intensive process management
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