New RSF Awards for 31 Projects Led by Young HSE Researchers

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The Russian Science Foundation (RSF) has completed its review of project proposals submitted for grants supporting early-career researchers. More than 850 projects have been selected for funding, including 31 from HSE University. The grants will finance research addressing specific objectives within the priorities of scientific and technological development set out in the Scientific and Technological Development Strategy of the Russian Federation.

Winners of the 'Initiative Research Conducted by Young Scientists' award include 18 projects in the fields of Humanities and Social Sciences, Engineering, Mathematics, Computer Science and Systems Sciences, and Physics and Space Sciences. The projects will be carried out from 2026 to 2028.

These researcher-initiated projects will be led by researchers under the age of 33. Where necessary, they may form research teams that include full-time students. Grants amount to up to 1.5 million roubles per project per year.

List of Projects

1. 'Generational and Confessional Differences in Russians’ Religious Education' by Oxana Mikhaylova.

2. 'Strategies for Adapting Russians’ Digital Engagement to Internet Sovereignty: Privacy Concerns and Political Attitudes as Determinants of Switching to Russian Media Platforms' by Maria Rodionova.

3. 'Russians’ Attitudes toward Justice Administration Policy: Development and Validation of a Survey Questionnaire, and the Role of Values and Sociodemographic Factors' by Nikita Zubarev.

4. 'Prospects for a New Security Architecture in the Sahara-Sahel Region and Russia’s Interests' by Aleksei Chikhachev

5. 'Factors Determining Residents’ Intentions to Stay in Russia’s Peripheral Cities' by Ekaterina Sharepina.

6. 'Studies of Actionality from a Typological Perspective' by Stepan Mikhailov

7. 'Development of Supply Optimisation Models for Digital Logistics Management Technologies' by Ivan Shidlovskii

8. 'Assessing the Economic Impact of AI Adoption in Russia' by Mikhail Miriakov

9. 'Investigation and Adjudication of Criminal Cases in 18th-Century Russia' by Anastasia Vidnichuk

10. 'Public Entities in Private Law: A Systematic Analysis and Ways to Improve Legal Regulation' by Viktor Eremin.

11. 'Factors Influencing the Development of Regional Service Exports amid Structural Transformation of the Economy' by Dmitry Kashin.

12. 'Models and Methods for Deploying Agentic AI on the Internet' by Anna Gaydamaka.

13. 'Regulation of DES Structure by Zwitterionic Osmolytes in Nanopores: Mean-Field Theory and Molecular Modelling' by Nikolai Kalikin.

14. 'Application of Sparse Attention Mechanisms in Deep Learning Architectures for Tabular Data' by Vera Ignatenko.

15. 'Intelligent Methods for Orchestrating Group Interaction in Educational Environments Using Generative AI Models' by Andrei Ternikov.

16. 'Determining Exact Values of Generalised Ramsey Numbers' by Dmitrii Taletskii.

17. 'Nonlinear Dynamics and Chaos in Models of Monopolistic Competition and Economic Growth' by Efrosiniia Karatetskaia.

18. 'Exciton–Polariton Condensates Based on Bound States in the Continuum in Single Perovskite Microstructures' by Daria Khmelevskaia.

It is noteworthy that the project ‘Models and Methods for Deploying Agentic AI on the Internet,’ led by Anna Gaydamaka, Research Fellow at the HSE Telecommunications Research Institute, is the first to have secured a qualified customer and co-financing.

Winners of the ‘Research by Teams Lead by Young Scientists’ award include 10 projects in the fields of Humanities and Social Sciences, Mathematics, Computer Science and Systems Sciences, and Chemistry and Materials Sciences. The projects will be implemented from 2026 to 2029.

The projects are carried out by teams of four to eight people, at least 70% of whom must be under the age of 39. Grants range from 3 million to 6 million roubles per year.

List of Projects

1. 'Cultural and Linguistic Dimension of Turkey’s Foreign Policy as an Instrument of Geopolitical Influence: Current Initiatives and Prospects' by Damir Islamov.

2. 'Conceptualising the Value Foundations of Russian Foreign Policy: The Role of Traditional Values in Its Implementation' by Alexander Girinsky.

3. 'Endogenous Factors Shaping the Transformation of the CFSP, CSDP, and EU Enlargement Policy through the Lens of the Multiple Streams Framework: Implications for Russia' by Sergey Shein.

4. 'What Makes Parents (Un)Happy? Family-Role Factors Influencing Parents’ Subjective Well-Being in Russia' by Ekaterina Nastina.

5. 'Developing a Multimethod Data Ecosystem: Integrating Digital Footprints, Metadata, and Survey Data to Improve Data Quality and Enrich Sociological Research' by Daniil Lebedev.

6. 'Studying Trends in the Development of Education in BRICS Countries Using Weak Signals Methodology' by Anastasia Andreeva.

7. 'Integrating New Methodological Developments in Inferential Network and Qualitative Analyses to Study Self-Organisation of Russian Society: Evidence from St Petersburg and Leningrad Oblast' by Dmitry Arkatov.

8. 'Combinatorial Approaches to the Study of Matrix Graphs, Matrix Words, and Composite Words' by Artem Maksaev.

9. 'Development and Application of Effective Machine-Learning Potentials with Explicit Consideration of Magnetic and Electrostatic Interactions' by Ivan Novikov.

10. 'Medieval Literature and Russia in the 18th-20th Centuries: Traditions, Connections and Cultural Dialogue' by Ksenia Soshnikova.

The Russian Science Foundation has also extended the deadlines for three projects in the fields of Humanities and Social Sciences and Mathematics, Computer Science, and Systems Sciences led by early-career researchers. The projects, which began in 2023, have been extended through 2026–2028. Grants range from 3 million to 6 million roubles per year.

List of Projects

1. 'Developing and Testing Methods for Automated Analysis of Russian Court Sentencing Texts for Socio-Legal Research: The Case of Violent Crimes' by Anton Kazun.

2. 'Agency of University Students and Graduates in the Labour Market: Typology, Determinants, Manifestations, and Effects' by Pavel Sorokin.

3. 'Algebraic-Geometric Methods in Field Theory and Other Applications' by Dmitry Shirokov.

Award winners told the HSE News Service about their projects.

Ekaterina Sharepina, Research Fellow at the Laboratory of Social and Demographic Policies at the Vishnevsky Institute of Demography, head of the project 'Factors Determining Residents’ Intentions to Stay in Russia’s Peripheral Cities'

— Research on internal migration usually focuses on why people want to leave small towns and rural areas. We suggest looking at the issue from the other side: why do some residents of peripheral cities choose to stay? This is particularly important for Russia, where the long-term population outflow from peripheral areas remains one of the key challenges. We want to understand how personal circumstances, government policies and actions, and the characteristics of the city itself contribute to people’s decision to stay.

Our research draws on unique data collected over many years of fieldwork in 25 small and medium-sized cities in Russia’s peripheral regions and combines qualitative and quantitative methods of analysis. We plan to study not only residents’ motivations but also the characteristics of the settlements themselves in order to understand how these factors interact. We hope that the project's findings will contribute to our understanding of the mechanisms that help retain population in peripheral areas.

Alexander Girinsky, Research Fellow at the International Laboratory for the Study of Russian and European Intellectual Dialogue, head of the project 'Conceptualising the Value Foundations of Russian Foreign Policy: The Role of Traditional Values in Its Implementation'

— The project addresses interdisciplinary issues at the intersection of political theory, philosophy, and applied research in international relations. Its main objective is to draw on approaches from various social sciences and humanities to conceptualise the notion of ‘traditional values’ in the context of contemporary Russian foreign policy. Although this concept has been widely used in political discourse in recent years, many theoretical questions remain unanswered. Our project seeks to address these questions.

We are primarily interested in whether the idea of traditional values can become Russia’s global value proposition and whether it has the potential to develop into a new, inclusive ideology of global development and cooperation in a future multipolar world. We expect our work not only to contribute to the historical and theoretical understanding of foreign policy but also to help shape practical approaches to advancing Russia’s national interests.

Anastasia Andreeva, Head of the Laboratory for Educational Innovation Research at the Institute of Education, head of the project 'Studying Trends in the Development of Education in BRICS Countries Using Weak Signals Methodology'

— Our project focuses on identifying educational trends in the BRICS countries and developing a tool for forecasting changes in education based on so-called weak signals—early indicators of emerging change found in innovative practices, professional communities, educational initiatives, and public discussions.

The project will place particular emphasis on grassroots innovations—initiatives that emerge not only at the level of public policy but also in universities, schools, startups, professional communities, and educational projects. One of the project's data sources will be the Educational Innovation Competition organised by HSE University for more than 13 years.

In addition, we will analyse national education development strategies, international analytical materials, and international competitions in educational innovation. AI will be used to process large volumes of data and identify weak signals, while the findings will be supplemented by interviews with experts and representatives from BRICS countries.

The project will result in a methodology for monitoring educational trends, a tool for analysing weak signals, an open-access database, and a web-based dashboard providing access to the research findings. Recommendations developed as part of the project will help education authorities, universities, and research organisations make more informed strategic decisions, strengthen international cooperation, and respond promptly to emerging challenges and opportunities in education.

Artem Maksaev, Associate Professor, Deputy Head of the Laboratory of Theoretical Computer Science at FCS, head of the project 'Combinatorial Approaches to the Study of Matrix Graphs, Matrix Words, and Composite Words'

— The project focuses on fundamental research at the intersection of algebra, combinatorics on words, and graph theory. We study numerical invariants of associative algebras and special classes of graphs associated with these algebras. Our main goal is to develop new methods and solve a number of open problems.

Our research is in pure mathematics, but even in this field, potential applications can be found in areas ranging from coding theory to biology. I have never previously led an RSF grant, although our team has experience in successfully implementing grants on related topics. This role carries significant responsibility, and we have already started working on the project.

Ivan Novikov, Associate Professor, Head of the Machine Learning in Atomic Modelling Research and Study Group at FCS, head of the project 'Development and Application of Effective Machine-Learning Potentials with Explicit Consideration of Magnetic and Electrostatic Interactions'

— Our project focuses on developing and applying machine-learning methods to computational materials science, in particular for developing machine-learning interatomic potentials. These mathematical models are trained on computationally intensive quantum-mechanical calculations and enable us to determine material properties through computer simulations with high accuracy and within a reasonable amount of time.

The project will develop two families of machine-learning potentials: those incorporating magnetic degrees of freedom and those explicitly accounting for long-range interactions. The first type will enable researchers to study magnetic materials, such as structural alloys, and predict their properties, while the second will be particularly important for describing materials such as perovskites and organic compounds.

The idea for this project was proposed by a research team that has been developing machine-learning potentials for more than 10 years at an internationally competitive level. The team includes researchers from HSE University’s Faculty of Computer Science and Faculty of Chemistry, as well as Skoltech. I previously received a grant and led a similar project from 2022 to 2025.

As part of the grant and in future work, the research team plans not only to develop magnetic machine-learning potentials and models that explicitly account for long-range effects in order to address new classes of problems and describe new materials, but also to develop algorithms for more efficient training based on linear algebra methods.

One-third of the grants awarded through the three RSF competitions went to early-career researchers from the HSE campuses in St Petersburg, Nizhny Novgorod, and Perm. More information about the projects to be carried out at HSE University–St Petersburg can be found here.