• A
  • A
  • A
  • ABC
  • ABC
  • ABC
  • А
  • А
  • А
  • А
  • А
Regular version of the site

HSE Strategic Technological Projects in 2025

HSE Strategic Technological Projects in 2025

© iStock

In 2025, HSE University continued its participation in the Priority 2030 Strategic Academic Leadership Programme, maintaining a strong focus on technological leadership in line with the programme’s updated framework. A key element of the university’s technological leadership strategy is its Strategic Technological Projects (STPs), aimed at creating in-demand, knowledge-intensive products and services.

A distinctive feature of the Strategic Technological Projects is the development of research-based products built on the university’s existing expertise and groundwork. STP teams implement projects with strong demand potential from society, business, and government, in line with Russia’s priorities for scientific and technological development. An important change in 2025 was the centralisation of STP management, which made it possible to integrate them more effectively with other initiatives aimed at achieving HSE University’s technological leadership goals.

Forecasting and Foresight: Capitalising on Expertise

To support evidence-based decision-making by government bodies and businesses, the STP team of the National Centre for Science, Technology, and Socio-Economic Foresight develops advanced systems analysis and forecasting technologies. These technologies are classified as critical under Presidential Decree No. 529 of June 18, 2024.

In 2025, the team focused on further developing existing expert and analytical products and creating new ones. In particular, a unique team of leading experts updated the scenario-based forecast of Russia’s socio-economic development. The resulting report, Scenarios for the Development of the Russian Economy in the Context of Geopolitical Turbulence, was prepared by HSE University across 14 key economic and social sectors with the participation of more than 150 leading specialists. The forecasting horizon was extended to 2036, and the system of scenarios was revised and adapted to the new global environment. The report has been in high demand among major private and public-sector organisations. The report is complemented by consensus forecasts covering key areas of socio-economic and scientific and technological development. These are updated annually based on surveys conducted among a unique panel of more than 700 experts.

Another important decision-support tool is a set of databases covering a wide range of areas, from investment projects in agriculture and the IT sector to trends in the green economy and international sanctions. In 2025, two new databases were created: a navigator of promising competencies for the digital economy and a database of global defence-industry production chains. Six other databases launched in 2024 were updated, including interface improvements and the addition of new user-friendly features.

© iStock

The STP team also expanded its range of regular analytical reviews. Since June 2025, it has been monitoring the agendas of leading global think tanks in three key areas: scientific and technological development and innovation, the global economy, and foreign policy and security. On a regular basis, the team publishes reviews of current Russian and international forecasts, as well as information bulletins entitled Trends. Events. Figures, which examine developments in Russia and worldwide across 14 key sectors of the economy and social sphere.

New Priorities: 6G Communication Technologies

The Strategic Technological Project (STP) ‘Trusted 6G Communication Systems Technology Suite’ focuses on developing domestic technologies for the design and production of sixth-generation communication equipment. The need for such technologies is driven by Russia’s priorities in scientific and technological, economic, and spatial development. The targeted deployment of 6G technologies is expected in the near future, and HSE University therefore aims to establish its own scientific and technological foundation in this field.

The project is being implemented at the Telecommunications Research Institute established at the end of 2024. The inclusion of this project in the university’s portfolio of strategic technological projects represents a new challenge within the updated development programme, aimed at supporting and ensuring the sustainable growth of HSE’s engineering capacity. The STP is based on an approach that combines the development of highly intelligent trusted 6G technologies with their engineering implementation on a domestic digital platform. In 2025, the team’s efforts focused on creating key elements of the electronic component base for 6G radio communication systems.

The STP team is developing a digital platform for the design and testing of 6G technologies, which will accelerate the development and prototyping of electronic components through the use of digital twins. Technical solutions have been created in key areas, including interference-resistant coding, information protection algorithms, multiple-access methods, and network resource management. In addition, prototypes of smart radio environment elements based on silicon and III–V semiconductor microelectronics have been developed. These elements are capable of adapting to changing conditions and controlling signal propagation characteristics. The team’s results were presented at the ITMO Wireless: High-Frequency Wireless Technologies school and conference. The project team is already involved in implementing sectoral projects commissioned by the Russian Ministry of Digital Development, Communications, and Mass Media.

Artificial Intelligence: From Model to Agent

The STP ‘Multi-Agent AI Platform for Sectoral Solutions’ is being developed along two main lines: the creation of infrastructure for developing, deploying, and ensuring access to AI models, and the development of AI agents for various sectors of the economy and the social sphere. In 2025, the functionality and user interface of the SmartMLOps platform for hosting and managing AI services were significantly upgraded. The platform is integrated into the university’s digital infrastructure to accelerate the development and market introduction of AI services and is already being used by HSE researchers to deploy AI models and access data.

© iStock

An interactive platform is also under development, enabling users to find and access AI services for research, analytical, and sector-specific tasks. At the same time, university researchers and developers will gain a convenient tool for transferring their innovations to practical use. The platform is being built on the basis of the iFORA (Intelligent Foresight Analytics) system.

Alongside infrastructure development, AI assistants for various industries are being created. HSE experts continue to work on tools for managing climate risks. In 2025, the project team proposed a methodology and developed a database of climate risk profiles for municipalities, containing information on hazardous natural phenomena and the threats they pose to the economy and population. These developments were presented at Russian and international forums, including the UN AI for Good Summit in Geneva. The researchers regularly publish analytical materials, such as a report on financial solutions for climate adaptation in Russia. Banks, companies, and public authorities can use these results to assess climate risks and develop adaptation measures.

In the context of a shortage of qualified personnel, companies and public authorities need tools for analysing the labour market in real time. In response to this challenge, the STP team has developed a prototype of the Labour Market Capacity analytical information system. The service automatically collects and analyses data on job vacancies, job seekers’ CVs, as well as regional socio-economic and demographic indicators. Its use will make it possible to monitor changes in regional labour markets quickly and effectively, including workforce mobility and supply-and-demand dynamics for specific professions.

Another important area of work is the development of AI agents to improve efficiency and introduce human-centred management principles within HSE itself. The STP team has created an ‘AI employee of the academic office’—a chatbot that advises students and teachers on academic organisation, research activities, and extracurricular matters. The system is currently being comprehensively integrated into the university’s digital ecosystem. Another AI service is designed to monitor students’ psychological and academic well-being. Its implementation will make it possible to predict risks and develop recommendations to support students who find themselves in difficult situations.

Increasing Technological Maturity and Developing Partnerships: Plans for the Coming Year

The launch of strategic technological projects in 2025 not only set new research challenges for the university, but also required a special focus on the transfer of technological products and services. Most STPs are based on strategic projects implemented at HSE between 2021 and 2024. Today, capitalising on intellectual potential is one of the university’s key strategic objectives. Therefore, in 2026 the work of STP teams will focus both on increasing the technological maturity of their solutions and on attracting industrial partners. At the same time, the search for new ideas for technological development within the STP framework continues. In December 2025, an open call for ideas for the development of AI agents was launched. Selected projects will receive expert and technological support.

Elena Odoevskaya, HSE Vice Rector

‘In 2025, HSE confirmed its leadership in the updated Priority 2030 programme. The university’s strong performance in the programme also reflects the success of its strategic technological projects. Some of them are still at an early stage, while others have already reached a high level of maturity. In some areas, we need to intensify our search for markets and partners ready to implement our developments at an industrial scale; in others, we are already integrating them into our day-to-day operations. Our researchers are not only successfully advancing unique expertise in socio-economic forecasting, foresight, and AI technologies, but are also developing new competencies in telecommunications and engineering. We understand that these projects require special attention, as they involve a significant part of our community of experts, researchers, and developers, even though many other important initiatives are also being implemented at HSE within the Priority 2030 programme. Given HSE’s achievements in the programme, we can say that the teams’ developments contribute to the university’s technological leadership goals and make a substantial contribution to the implementation of national technological leadership projects.’

See also:

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.

Biologists Discover Unique Properties of MiR-93-5p MicroRNA in Prostate Cancer

Researchers at the International Laboratory of Microphysiological Systems of the HSE Faculty of Biology and Biotechnology investigated how different isoforms of the same microRNA influence gene function in prostate adenocarcinoma. The study found that in some cases, microRNAs can reinforce each other’s effects by targeting and suppressing the same genes. This finding offers a fresh perspective on the molecular mechanisms underlying tumour development and on the search for disease biomarkers. The results have been published in PeerJ.

Researchers Discover How Spelling Errors Slow Down Reading in Russian

Psycholinguists from the Centre for Language and Brain at HSE University–St Petersburg have shown that words that are frequently misspelled are processed more slowly by readers, even when presented with the correct spelling. The researchers confirmed this effect for the first time using Russian-language materials and found that response speed is most strongly linked to how confidently individuals can distinguish the correct spelling of a word from an incorrect one. The study has been published in The Mental Lexicon.

Scientists Discover Why Europium 'Misbehaves'

Europium is a rare-earth metal responsible for the pure red glow in displays and other luminescent materials. For a long time, however, it refused to emit light when surrounded by certain organic molecules known as acylpyrazolone ligands. Chemists have now uncovered the reason: in europium complexes with these ligands, a 'black window' appears—a charge-transfer state in which the energy absorbed by the ligand is dissipated as heat rather than emitted as light. Understanding this mechanism opens the way to designing more efficient red-emitting materials for displays, fluorescent thermometers, and chemical sensors. The results have been published in Dalton Transactions.

HSE Economists Reveal How the Wage Gap Emerges Among Vocational School Graduates

HSE researchers examined the careers of 600,000 graduates of Russian secondary vocational education programmes and found that at the start of their careers, the gender wage gap reaches 23%, doubling after three years. This disparity is largely due to male and female students choosing different occupations when enrolling in vocational schools. These were the findings made by Sergey Roshchin, Natalya Yemelina, and Ksenia Rozhkova from of the HSE Faculty of Economic Sciences. The article has been published in Educational Studies.

HSE Researchers Make Aldehydes Perform Dual Function

Chemists from HSE University have discovered a way to carry out a reductive addition reaction without using an external reducing agent. Instead, the required 'resource' is supplied by the aldehyde itself, one of the reaction participants. This approach helps prevent unwanted side reactions, reduces toxicity, and simplifies the production and synthesis of organic molecules, including those used in the manufacture of medicines. The study has been published in Journal of Catalysis.

HSE & VK Engineering and Mathematics School Showcases 13 Projects at 10th Demo Day

The 10th Demo Day of the Joint HSE & VK Engineering and Mathematics School was held at the VK Moscow office. Students of the three workshops presented the results of 13 projects in the fields of artificial intelligence, information security, and digital platforms. Students worked on the development of recommendation services, systems for psycholinguistic text analysis and speech processing, methods for identifying celebrities in videos, algorithms for determining the toxicity of memes, security mechanisms for AI systems, and approaches to improving the effectiveness of neural network models.

Tabular Data Anonymisation Solution for Safe Use in AI Systems Developed at HSE University

The AI and Digital Science Institute at the HSE Faculty of Computer Science has developed a tabular data anonymisation service designed to prepare corporate datasets for use in analytics and AI applications. The solution can identify personal data in structured datasets, apply consistent and reproducible anonymisation rules, and generate the artifacts required for quality control, auditing, and subsequent use of data in secure environments.

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.

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.