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News
September 25, 2026
AI Users Earn Up to 41.8% More Than Non-Users
Research conducted by economists at HSE University has revealed a significant correlation between the regular use of GenAI in the workplace and higher pay among Russian employees. The study found that individuals who frequently use GenAI in their professional activities earn notably more than those who reject these new tools or resort to them occasionally. The salary premium for highly qualified specialists reaches 41.8%. The article was published in the Voprosy Ekonomiki journal.
September 24, 2026
‘Feedback and Constructive Criticism Are Essential in Our Profession
Vincent Fardeau, Associate Professor at HSE ICEF, has reached a major career milestone: he recently published his paper ‘Asymmetric Thin Markets’ in the Journal of Financial Economics, successfully passed his major academic review, and received tenure. In this interview, Vincent discusses the story behind the paper, explains the concept of asymmetric thin markets, and shares his advice for young scholars aiming to publish in top-tier journals.
September 22, 2026
Personal Interest in Doctoral Thesis Topic Most Important for Confidence in Successful Defence
A researcher at HSE University analysed data on 1,539 doctoral students from 161 Russian universities to identify which features of a thesis topic are associated with academic success and engagement. The most important factor was found to be personal interest in the research topic, which was associated with almost all key aspects of doctoral programme experience—from engaging with the academic supervisor to research activity and confidence about successfully defending the thesis. The findings have been published in Higher Education.

 

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Система поддержки принятия решений для рационального озеленения города на примере г. Ереван, Республика Армения

Программная инженерия. 2019. Т. 10. № 2. С. 87–96.
Akopov A. S., Beklaryan A., Сагателян А. К., Саакян Л. В., Беляева О. А., Тепяносян Г. О.

This article presents the developed decision support system for the rational management of landscaping on the example of Yerevan, Republic of Armenia. Using agent-based modeling methods, a simulation model has been developed for the distribution of emissions of harmful substances into the atmosphere, taking into account their interaction with green plantings (trees) in order to minimize the concentration of harmful emissions in protected (socially significant) areas, in particular, in kindergarten areas. An important element of the developed system is the proposed genetic algorithm for real coding, aggregated with a simulation model of emission propagation, implemented on the AnyLogic platform. As a result of numerical experiments, the best configuration of tree planting around kindergartens in Yerevan has been obtained, ensuring the minimum level of concentration of harmful substances in the respective protected areas, taking into account the restrictions on the cost of the greening program. The developed software complex allows for: further detailing of the emission distribution simulation model; modeling strategies for vertical gardening (i.e., landscaping walls and roofs); clarification of the methodology for predicting the dynamics of the spread of harmful emissions; development of the software complex as a decision support system for environmental planning, taking into account the density of residents distribution, and remoteness of urban buildings from industrial enterprises and traffic flows (roads) in the formation of an optimal greening strategy.

Research target: Earth Sciences Computer Science Mathematics
Priority areas: IT and mathematics
Language: Russian
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Keywords: имитационное моделированиегенетический алгоритмsimulation modelingGreeningэкологическое моделированиеgenetic algorithmозеленение городаharmful emissionsenvironmental modelingвредные выбросы
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