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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.
September 21, 2026
Researchers Develop Methodology to Assess the Quality of Legal Representation in Criminal Proceedings
Having a good defence attorney in criminal proceedings can largely determine whether a defendant retains their freedom, health and good name. Researchers at HSE University propose a method for predicting an attorney’s performance based on the outcomes of their previous cases. The methodology takes into account the severity of the charges, the complexity of the cases, and the most likely outcome, drawing on judicial statistics.
September 21, 2026
Algebra, Geometry, and AI: Russian and Vietnamese Mathematicians Discuss Current Research
A delegation of scientists from Hanoi visited the HSE Faculty of Computer Science and then took part in a Russian-Vietnamese conference in St Petersburg. The events were part of the three-year project ‘Flexibility and Computational Methods.’ Over the course of the project, the researchers have prepared joint publications and obtained new mathematical results.

 

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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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