Scientists Explain How Emotions Shape Attitudes Toward Digital Governance
Today, interactions between citizens and government increasingly take place through digital governance platforms, including digital public services, AI-powered systems, and algorithmic decision-making tools. Until now, however, these technologies have largely been viewed as technical instruments, with their effectiveness assessed primarily in terms of efficiency and user-friendliness. The authors of a new study propose a broader perspective, arguing that digital governance should also be understood as an emotional experience that directly shapes citizens' trust in public institutions.
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HSE in Minsk: Developing Cooperation with Belarus
On May 26–29, 2026, an HSE University team visited Minsk, the capital of Belarus. The purpose of the trip was to meet and hold talks with Belarusian universities and scientific organisations—HSE University's current and prospective partners.
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‘HSE University Provides Students with a Springboard into a World of Opportunities’
In 2024, Ikenna Mbata, from Owerri, Nigeria, enrolled on the Master’s in Science, Technology and Innovation Management and Policy at ISSEK in Moscow. After two years of studies, on June 1, 2026 he successfully defended his master’s thesis ‘The Spatial Distribution of Pharma Start-ups in Africa: An Analysis of Innovation Clusters and Policy Drivers.’ In his interview with the HSE News Service, Ikenna speaks about his research topic, the role of HSE University in shaping his skills, the importance of volunteering, and the benefits of studying in an international environment.
Neural Network Maps as a Method for Constructing Mathematical Models
Scientists from HSE University–Nizhny Novgorod and the Institute of Physics Belgrade, Serbia, are jointly exploring the application of machine learning techniques and neural networks to the study of nonlinear dynamics. Natalya Stankevich, Leading Research Fellow at the Laboratory of Topological Methods in Dynamics of the Faculty of Informatics, Mathematics, and Computer Science at HSE University–Nizhny Novgorod, spoke to the HSE News Service about this international project.
A Future for Everyone: ‘Eurasia Is an Excellent Space for Building Reliable Supply Chains’
At the 2026 St Petersburg International Economic Forum, participants examined the global economy, trade and logistics in turbulent times, as well as the role of pension savings in Russia. Here are highlights from the sessions featuring HSE University experts.
‘In the Age of Technology, It Is Interesting to Look into the Past and Think about What We Can Take from It’
Polina Tabakova decided to apply for a Philology degree at HSE in Nizhny Novgorod because she grew up in Mari El and did not want to move far away from the Russian forests. In an interview for the Young Scientists of HSE University project, she spoke about the genre of the campus novel, the existential drama of Kolobok, and a blackout version of Eugene Onegin.
HSE Scientists Develop Method to Compress Large Language Models Without Losing Quality
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science have developed a new compression method for large language models such as GPT and LLaMA that reduces their size by 25–36% without additional training or significant loss of accuracy. This is the first approach to use mathematical transformations—specifically, rotations of model weights—to make models more amenable to compression with structured matrices. The study results have been published in ACL Findings 2025. The code is available on GitHub.
How HSE International Relations Students Intern at UN Economic Commission for Africa
This year, third-year students of the International Relations programme Arsenii Armanshin and Arkady Tsvetkov travelled to Addis Ababa, Ethiopia, as part of the Africa Track. They secured internships with the United Nations Economic Commission for Africa (UNECA). In an interview with the HSE News Service, they spoke about their journey, work responsibilities, and the experience they gained.
‘Academic Counterpart to SPIEF’ Took Place at HSE University–St Petersburg
From May 18 to 22, HSE University–St Petersburg became the centre for global academic dialogue. This was the third time the city hosted International Partners' Week, a strategic event of HSE University. The event brought together more than 100 delegates from 45 universities and 20 countries. Participants shared their impressions of the forum and HSE University.
Machine Learning Models Can Help Reduce Volatility and Boost Stock Market Returns
The use of machine learning models makes it possible to achieve greater accuracy in predicting risks in the Russian stock market compared to classical econometric approaches. The predictive power of these models increases by 23%, while the average investor’s return can reach up to 13% per annum. These conclusions were drawn by Nikita Lysenok from the Department of Financial Market Infrastructure at the HSE Faculty of Economic Sciences. The paper has been published in Fundamental and Applied Mathematics.