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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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Hardware-Software Complex for Network-on-Chip Prototyping Using Multiple FPGAs

IEEE Access. 2026. Vol. 14. P. 7921–7931.
Mikhail Y. Romashikhin, Aleksandr Y. Romanov

This paper presents a hardware-software multi-FPGA complex designed for hardware prototyping of networks-on-chip (NoCs). The rationale for the use of multiple FPGAs for NoC prototyping is given. The architecture of the complex and its components–the software part generating top-level files and configuration files describing the NoC for several FPGAs, hardware part consisting of interfacing switches between FPGAs, SoM modules with FPGAs, printed circuit board connecting the modules by a data bus–were developed. The work of the multi-FPGA complex developed was tested by calculating the examples of parallel computing tasks. The calculation of 100 digits of the π number by the Madhava series, Monte-Carlo method, and solution of the system of linear equations were chosen as a task of parallel calculations. The evaluation of benchmark developed showed that the multi-FPGA complex is suitable for NoC prototyping of parallel calculations and can be used in solving a variety of engineering problems besides NoC prototyping.

Research target: Electronics and Electrical Engineering Computer Science
Language: English
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Keywords: автоматизация проектированияпараллельные вычисленияparallel computingdesign automationFPGAПЛИСпрототипированиеСистема на кристаллесеть на кристаллеsystem-on-chipNoC benchmark network-on-chip prototyping
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