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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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О некоторых нижних оценках числа ребер в трехсвязных гиперграфах и их достижимости

Успехи математических наук. 2026. С. 1–2.
Дидин М. А., Malyshev D.
In press
Language: Russian
Keywords: экстремальная комбинаторика
Publication based on the results of:
Network and graph models, algorithmic complexity and data mining (2025)
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The paper formulates Zarankiewicz problem in terms of formal contexts as follows: What is z(m, n; s, t), the largest size of the incidence relation of a formal context with m objects and n attributes, for which there is no a formal concept with the given extent s and t intent sizes and larger? Exact formulas for ...
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