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News
October 8, 2026
HSE Experts Take Part in 23rd Annual Meeting of Valdai Discussion Club
The 23rd Annual Meeting of the Valdai Discussion Club was held from September 28 to October 1, 2026 under the theme ‘Responsibility for the Future: Limits of the Possible, or Limitless Possibilities?’ The forum brought together 120 experts from 40 countries, including representatives of China, the United States, India, Brazil, the United Kingdom, Germany, Egypt, Iran, and Japan.
October 7, 2026
‘Our Team Consists of True Leaders in Their Respective Academic Disciplines
The HSE International Centre of Decision Choice and Analysis studies a wide range of methods for analysing decision-making and possible scenarios for the development of natural, socio-economic, and political phenomena using various mathematical models. The application of advanced mathematical methods to forecasting helps to prevent negative outcomes and avoid erroneous decisions. The HSE News Service spoke to the centre’s director, Prof. Fuad Aleskerov, about its work.
October 6, 2026
International N5 Symposium ‘Neural Networks and Nonlinearity in Nizhny Novgorod Brings Together Scientists from Russia and Serbia
The International N5 Symposium ‘Neural Networks and Nonlinearity in Nizhny Novgorod’ was held at the Nizhny Novgorod House of Scientists from September 23 to 26. The event was organised by HSE University–Nizhny Novgorod and the Nizhny Novgorod House of Scientists, with the participation of Sberbank and the Institute of Physics Belgrade. The symposium was held for the second time: the first conference took place in 2025 and attracted considerable interest from the academic community.

 

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Перспективные направления совершенствования процессов жизненного цикла разработки программного обеспечения

Прикладная информатика. 2024. Т. 20. № 2.2025. С. 79–96.
Stoyanova O., Окусков И. С.

The article explores the ways to increase the operational efficiency of IT
companies by improving approaches to solving tasks at different stages of the software
development life cycle (SDLC). It is shown that the greatest potential for growth of operational
efficiency lies in the tasks of the stage of processing requirements. Automation of these tasks
via artificial intelligence tools, especially those based on large language models (LLM), will
significantly reduce the duration of SDLC by cutting the number of iterations for rework and
error correction. The paper analyses the capabilities of such tools, as well as the complexities
associated with their implementation, including the risk of technological dependence, the
problems of integrating new tools into the current IT landscape of companies, the risks of
disrupting the continuity of processes during implementation, as well as the difficulties of
assessing the economic effects. The paper concludes that a comprehensive approach to SDLC
modernisation is needed, which should combine technological innovation with organisational
changes in the form of transformation of corporate culture and processes aimed at adapting to
new technologies. Directions for further research are suggested, including the development of
universal methodologies for implementing AI tools and models for assessing their economic
efficiency.

Research target: Economics and Management Engineering and Technology
Language: Russian
Full text
DOI
Text on another site
Keywords: искусственный интеллектоперационная эффективностьИТ-компанияIT companyoperational efficiency artificial intelligencesoftware development life cycleжизненный цикл разработки программного обеспечения
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