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July 16, 2026
Team Success: Aligning Means with Objectives
In corporations, sports, and academia, people often face challenges they cannot handle alone. In such cases, selecting the right team is crucial. Tatiana Mayskaya, Associate Professor at the HSE Faculty of Economic Sciences and the International College of Economics and Finance, together with colleagues from foreign universities, examined team characteristics and found that less diverse teams are better suited to objectives where a high average performance is important, whereas more diverse teams are preferable when avoiding failure is critical. The paper has been published in Economic Theory.
July 15, 2026
Economists Propose More Effective Approach to Reducing Smoking
Economists at HSE University have examined how smokers respond to changes in cigarette prices. When tobacco prices increase, cigarette consumption does not always decline. In fact, spending on tobacco may even rise: according to the researchers, a 1% decrease in cigarette affordability leads to a 0.28% increase in per capita tobacco expenditure. The findings suggest that to reduce smoking rates, tobacco prices must rise faster than household incomes. The study has been published in Voprosy Statistiki.
July 15, 2026
HSE MIEM Students to Develop Two Satellites from Scratch for Orbital Experiments
The devices, created by student teams, will conduct space research on the properties of promising solar cells, on-board energy storage systems, and serial electronics for student satellites.

 

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Развитие научной школы искусственного интеллекта в пермских университетах: история и научный приоритет (обзорная статья)

Прикладная математика и вопросы управления. 2018. № 4. С. 99–130.
Yasnitsky L.

The article is based on the annual Perm All-Russian scientific and practical conference "Artificial intelligence in solving urgent social and economic problems of the XXI century" (http://www.permai.ru/files/26.05.2018.pdf). It is also a brief overview of the results of the Perm branch of the Scientific Council of the Russian Academy of Sciences on the methodology of artificial intelli- gence, as well as several departments of the Perm state University, Perm state humanitarian pedagogi- cal University, National research University Higher school of Economics, Perm state medical University. The review covers the works that develop and apply the methods of artificial intelligence in the classical sense, i.e., those methods that simulate human intellectual activity by simulating natural mechanisms.

 

 

These are expert systems, genetic algorithms, neural networks, fuzzy mathematics. The scientific priori- ty of Perm scientists in the development of theoretical foundations and practical applications of artificial intelligence is emphasized.

Keywords: Artificial intelligence, neural network, expert system, genetic algorithm, theory, prac- tice, modeling, forecasting, optimization, recognition, data processing, knowledge extraction.

Research target: Computer Science Mathematics Mechanics and Mechanical Engineering Medical Technologies Clinical Medicine Psychology Economics and Management Education Sociology (including Demography and Anthropology Political Science, International Relations, and Public Administration Other Humanities
Priority areas: mathematics
Language: Russian
Full text
DOI
Text on another site
Keywords: искусственный интеллектобзорartificial intelligenceискусственная нейронная сетьArtificial Neural Network (ANN)Scientific priorityнаучный приоритет
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