HSE University and Sber Conduct Foresight in Artificial Intelligence
HSE University, in collaboration with Sber, have conducted a foresight study on artificial intelligence (AI). Its early results were discussed by the participants of a strategic foresight session on exploratory research in AI, held at the Coordination Centre of the Russian Government, headed by Deputy Prime Minister Dmitry Chernyshenko. The results from the foresight study will inform the Unified Research and Development Programme in the Field of AI.
Foresight refers to large-scale studies designed to identify promising areas for the development of science and technology that can impact the economy and society in the medium and long term. Foresight focuses not only on evaluating potential scenarios for science and technology development but also on selecting the preferable ones by involving key stakeholders and leading scientists from various scientific schools to build a coordinated position. Expert assessments (qualitative methods) form the basis for evaluating future options, while quantitative methods and big data analysis are also among the foresight techniques. AI foresight is a type of industry-level foresight. In addition, the HSE Institute for Statistical Studies and Economics of Knowledge (ISSEK) conducts foresight studies at the national, international, and corporate levels.
Work on AI foresight started in February 2024, almost simultaneously with the approval of the updated National AI Development Strategy for the period until 2030. More than 50 of the most esteemed experts in the field, representing business and government, participated in the study. Addressing the Coordination Centre's session, Mikhail Skvirsky, Managing Director at Sberbank PJSC, and Leonid Gokhberg, First Vice Rector and Director of ISSEK at HSE University, shared the objectives and progress of the foresight study.
HSE University was tasked with providing the foresight methodology. The study design was determined, in particular, based on key features of the AI field, such as its high dynamism and rapid implementation of scientific results into new products and services, Professor Gokhberg explained.
The task of identifying promising research areas in the field of AI was accomplished within an extremely short timeframe, spanning from February to May. During this period, the foresight organisers conducted an analysis of global trends and markets, scientific frontiers, and growth points, and also a series of surveys, expert interviews, and foresight sessions which involved leading Russian researchers in the field of AI.
The foresight analysis resulted in a three-level classification describing exploratory research in the field of AI. This classification includes ten key areas (such as fundamental and generative models, machine learning architectures and algorithms, security, trust, and explainability of AI), along with 37 subareas and 127 research tasks.
Maxim Kolesnikov
The results from the foresight analysis will form the foundation of the Unified Research and Development Programme in the Field of AI, according to Deputy Minister of Economic Development of the Russian Federation Maxim Kolesnikov. Additionally, it was decided to recommend the Russian Academy of Sciences (represented at the session by its President Gennady Krasnikov) to use the obtained results, starting from 2025, in the selection of exploratory research and examination of incoming research applications.
Maxim Kolesnikov also highlighted that support for flagship research centres in the field of AI, selected within the framework of the first wave, will end in 2024, and to ensure seamless financing of research in this area, new centres (of the third wave) will soon be selected. He emphasised that this would indeed entail 'a new selection, rather than an automatic extension of support for existing centres.'
The primary parameters of the new selection include conducting basic research on priority topics aligned with the results of foresight, implementing applied research commissioned by industry partners, and facilitating the training of scientific specialists.
Dmitry Chernyshenko
'Artificial intelligence has become the driving force behind industries aimed to ensure the development of the supply-side economy. Simultaneously, with the emergence of large language models, our focus is increasingly on supporting basic science. Specifically, we have established AI research centres and have started using them to train scientists who will specialise in adapting generative AI to meet the requirements from various industries. This collaboration will enable us to attain technological leadership while enhancing the quality of people's lives, generating new employment opportunities, and bolstering the competitiveness of the economy.'
See also:
Researchers Develop Method for Direct Generation of Regulatory DNA
Researchers at HSE University have developed a model for generating promoters and enhancers—DNA sequences that regulate gene activity. The model works directly with DNA nucleotides, without first transforming them into a continuous numerical representation. This solution could be useful for applications in synthetic biology and gene therapy. The study results were presented at the ICLR 2026 Workshop ‘Generative AI in Genomics (Gen^2): Barriers and Frontiers.’
Researchers at HSE University and Sber Train Neural Networks to Better Predict User Preferences
The HSE FCS AI and Digital Science Institute and Sber have introduced a new architecture for recommendation systems that combines two classes of models, enabling algorithms to better predict users’ interests and needs. A preprint of the paper has been published on arxiv.org and presented at Urban ML.
‘Working with AI Solves a Wide Range of Engineering Problems’
Artificial intelligence is a working tool based on a balanced combination of algorithms and engineering. Experts and doctoral students from the HSE Moscow Institute of Electronics and Mathematics explain how AI technologies can improve an application, device, or system, and what engineering tasks are solved in the process.
A New Section on AI and a Prizewinning Paper: Early-Career HSE Researchers Take Part in IEEE EDM Conference
The 27th IEEE International Conference of Young Professionals in Electron Devices and Materials (EDM) has taken place in the Altai Republic. This year, researchers from HSE University presented the results of their research and were involved in organising a new section on artificial intelligence. A paper by HSE master’s student Rodion Sidorenko was awarded third place in the research paper competition at the conference.
‘AI Enables Researchers to Tackle More Complex and Important Problems’
In late July 2026, Dmitry Rybin, a graduate of the HSE Faculty of Mathematics who is now working in China, used ChatGPT to disprove a longstanding mathematical hypothesis. In an interview with the HSE News Service, he discussed AI's ability to make discoveries in mathematics, reflected on his time at HSE University, and spoke about his doctoral research at the Chinese University of Hong Kong.
AI for Doctors: HSE Faculty of Computer Science Delivers Course for Russian University of Medicine Students
In June 2026, the HSE Faculty of Computer Science (FCS) completed a course on the use of artificial intelligence in medicine for first-year Paediatrics students at the Russian University of Medicine. The course was delivered with support from a grant awarded to HSE University under the Artificial Intelligence federal project, part of the national project ‘Data Economy and the Digital Transformation of the State.’
HSE University to Launch New AI Supercomputer
HSE University is preparing to launch its second supercomputer. The new cluster will be primarily dedicated to artificial intelligence (AI) workloads and will complement the existing cHARISMa supercomputer. It is scheduled to become operational by the end of 2026.
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.