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  • Диагностика дислексии с использованием методов искусственного интеллекта по данным движений глаз: обзор
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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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Диагностика дислексии с использованием методов искусственного интеллекта по данным движений глаз: обзор

Клиническая и специальная психология. 2023. Т. 12. № 3. С. 1–29.
Gracheva M., Shalileh S.

The review considers methods of dyslexia diagnostics based on eye movement data and implemented on the basis of artificial intelligence. A number of studies have shown that eye movements in people with dyslexia may differ from those of people with normal reading abilities. Since 2015, studies have begun to appear in which the eye movements of observers with and without dyslexia were analyzed using various artificial intelligence methods. To date, there are a number of papers using both simple and more complex models (with neural networks and deep learning). This review discusses what accuracy of diagnosis has been achieved by researchers, for which groups of subjects and for which languages the current results have been shown, what types of algorithms have been used, and other practical aspects of conducting such diagnosis. According to the data analyzed, dyslexia diagnostics by eye movements and artificial intelligence methods is very promising and may have a significant impact on early diagnosing of reading problems.

Research target: Medical Technologies Computer Science
Language: Russian
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Keywords: искусственный интеллектeye-trackingдвижения глазeye movementsartificial intelligenceайтрекингдислексияdyslexiadiagnostics methodsметоды диагностики
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