Global AI Trends Discussed at International Foresight Workshop at HSE University
At an international foresight workshop on artificial intelligence held at HSE University, Russian and foreign scholars discussed the trends and challenges arising from the rapid development of AI.
The discussion centred on three key foresight areas: architectures, machine learning algorithms, and optimisation and mathematics; fundamental and generative models; governance, decision-making, and agent-based (multi-agent) models.
The event was organised by the HSE AI and Digital Science Institute, led by Director Alexey Naumov. Leading researchers from India, the UAE, and Germany took part in the workshop, together with heads of laboratories from the institute and other HSE divisions.
Foresight is a field of future studies that helps identify priorities for social, economic, and technological development, noted Alexander Sokolov, Director of the Educational Research and Educational Foresight Centre and Deputy Director of the HSE Institute for Statistical Studies and Economics of Knowledge (ISSEK), opening the discussion. ‘Foresight allows us to define the main challenges that are important in the global world. We see what changes are coming, which trends they will shape, how markets will evolve, and what technologies will be required for success,’ he said.
This year, ISSEK identified key trends in the development and dissemination of AI technologies, and this work is currently being updated. As part of this process, experts are taking part in interviews, foresight seminars, and data validation. The aim is to determine promising avenues for further AI research. A detailed report on the subject will be published at the end of 2025, Alexander Sokolov noted, inviting experts to contribute to its preparation.
Several speakers addressed machine learning, algorithms, and optimisation during the session. Among them was Maxim Rakhuba, Associate Professor at the HSE Faculty of Computer Science. ‘The high cost of training large neural network models makes the speed of this process a truly important parameter. Several promising methods were published last year, and I believe we can expect a rethinking and significant progress in this area in the near future,’ he said.
Aparajita Ojha, professor at the Indian Institute of Information Technology, Design, and Manufacturing, talked about the future of medical image analysis using generative technologies. Multimodal generative AI, she explained, accelerates the analysis of medical images. However, the technology is still at an early stage. ‘Neural networks are not making use of different methods, and some approaches are simply being ignored,’ she noted.
Denis Derkach, Head of the HSE Laboratory of Methods for Big Data Analysis, stressed that hybridisation in AI would soon be essential. This involves a comprehensive approach where different AI methods and technologies are combined with classical models to create systems that are more powerful and flexible than solutions based on a single methodology.
Incorporating scientific knowledge into AI models is one of the key ways of building reliable models in science, where data is always limited. At the same time, scientific knowledge can be expressed not only in mathematical formulae but also, for example, in information about which system parameters influence a response, said Michael Medvedev, Associate Professor at the HSE Joint Department of Organic Chemistry with the RAS Zelinsky Institute of Organic Chemistry.
The international foresight workshop at HSE University was organised in accordance with the decree of Russian President Vladimir Putin to hold a strategic session (an international foresight) in Russia on fundamental and exploratory research aimed at the further development of artificial intelligence.
See also:
HSE Students Among Winners of Yandex High-Tech Startup Accelerator
Yandex has announced the results of its Yandex AI Startup Lab accelerator, whose final round featured 12 IT projects. Over the course of three months, their creators—students and young entrepreneurs—worked alongside the company’s experts to develop their products. Four startups in digital marketing, medicine, and robotics were named the best, with their teams receiving cash prizes and cloud resource grants. Among them was Gradius, a startup founded by students from HSE University.
HSE to Bring Together Experts from World’s Leading Universities in St Petersburg
From May 18 to 22, 2026, HSE University–St Petersburg will become a hub of global academic dialogue. International Partners’ Week will bring together more than 100 delegates from 47 universities across 20 countries.
Researchers Find More Effective Approach to Revealing Majorana Zero Modes in Superconductors
An international team of researchers, including physicists from HSE MIEM, has demonstrated that nonmagnetic impurities can help more accurately reveal Majorana zero modes—quantum states considered promising building blocks for quantum computing. The researchers found that these impurities shift the energy levels that typically obscure the Majorana signal, while leaving the mode itself largely unaffected, thereby making its spectral peak more distinct. The study has been published in Research.
New Development by HSE Scientists Helps Design Reliable Electronics Faster at a Lower Cost
Scientists from HSE MIEM have developed a new approach to modelling electrothermal processes in high-power electronic circuits on printed circuit boards (PCB). The method allows engineers to quickly and accurately predict how electronic components heat up during operation, helping prevent overheating and potential failures. The results have been published in Russian Microelectronics.
The Future of Cardiogenetics Lies in Artificial Intelligence
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science have developed a program capable of analysing regions of the human genome that were previously inaccessible for accurate interpretation in genetic testing. The program adapts large generative AI (GenAI) models for cardiogenetics to predict how specific mutations affect the function of individual genes.
HSE and Peking University Discuss Prospects for Expanding Cooperation
In Moscow, HSE University’s leadership met with a delegation from Peking University headed by its President, Gong Qihuang. During the meeting, the parties agreed to strengthen partnership between the two universities within the framework of the Cross Years of Russian–Chinese Cooperation in Education (2026–2027).
New Foresight Centre Study Identifies the Most Destructive Global Trends for Humankind
A team of researchers from the HSE International Research and Educational Foresight Centre has examined how global trends affect the quality of human life—from life expectancy to professional fulfilment. The findings of the study titled ‘Human Capital Transformation under the Influence of Global Trends’ were published in Foresight.
HSE and Nazarbayev University: Scientific and Educational Cooperation
In April 2026, HSE University welcomed an official delegation from Nazarbayev University. The visit primarily focused on establishing cooperation between the two universities, expanding partnership ties, and developing joint projects in support of strengthening bilateral relations between Russia and Kazakhstan.
‘Meet Professors, Gain Experience’: Uzbek Lyceum Students Undertake Placement at HSE
The fourth off-site school organised under the Lyceum Classes project has taken place with the support of HSE University and implemented by the HSE Department of Internationalisation. This year, 79 students from International House Tashkent and Interhouse Lyceum came to HSE. The programme includes an introduction to the university, the opportunity to attend classes, and tours around Moscow.
HSE and Yandex Propose Method to Speed Up Neural Networks for Image Generation
A team of scientists at HSE FCS and Yandex Research has proposed a method that reduces computational costs and accelerates text-to-image generation in diffusion models without compromising quality. These models currently set the standard for text-to-image generation, but their use is limited by high computational loads, the company said in a statement.