Research & Expertise

An international team of scientists, including researchers from HSE University, has developed a new generative model called the Wyckoff Transformer (WyFormer) for creating symmetrical crystal structures. The neural network will make it possible to design materials with specified properties for use in semiconductors, solar panels, medical devices, and other high-tech applications. The scientists will present their work at ICML, a leading international conference on machine learning, on July 15 in Vancouver. A preprint of the paper is available on arxiv.org, with the code and data released under an open-source license.

The International Summer Institute on AI in Education has opened in Shanghai. The event is organised by the HSE Institute of Education in partnership with East China Normal University (ECNU). More than 50 participants and key speakers from over ten countries across Asia, Europe, North and South America have gathered to discuss the use of AI technologies in education and beyond.

In 1968, American mathematician Paul Chernoff proposed a theorem that allows for the approximate calculation of operator semigroups, complex but useful mathematical constructions that describe how the states of multiparticle systems change over time. The method is based on a sequence of approximations—steps which make the result increasingly accurate. But until now it was unclear how quickly these steps lead to the result and what exactly influences this speed. This problem has been fully solved for the first time by mathematicians Oleg Galkin and Ivan Remizov from the Nizhny Novgorod campus of HSE University. Their work paves the way for more reliable calculations in various fields of science. The results were published in the Israel Journal of Mathematics (Q1).

The AI and Digital Science Institute at the HSE Faculty of Computer Science hosted a conference focused on cutting-edge recommender system technologies. In an atmosphere of active knowledge sharing among leading industry experts, participants were introduced to the latest advancements and practical solutions in recommender model development.

Experts from HSE University took part in the BRICS Academic Forum (FABRICS) held in the capital of Brazil this year. The main theme of the event was to discuss cooperation among countries in the Global South amid geopolitical turbulence and rapid technological change. Academics and experts from BRICS member states and partner nations explored topics such as global healthcare, AI technologies, trade, climate change, and reform of the multilateral global security and governance architecture.

The International Laboratory of Algorithms and Technologies for Network Analysis (LATNA), established in 2011 at HSE University in Nizhny Novgorod, conducts a wide range of fundamental and applied research, including joint projects with large companies: Sberbank, Yandex, and other leaders of the IT industry. The methods developed by the university's researchers not only enrich science, but also make it possible to improve the work of transport companies and conduct medical and genetic research more successfully. HSE News Service discussed work of the laboratory with its head, Professor Valery Kalyagin.

The St Petersburg International Economic Forum took place on June 18-21, 2025. HSE experts have discussed cooperation between universities, investors, and technology companies in the development of innovations, sharing the best practices in healthcare and drug safety, as well as charity and humanitarian collaboration in the BRICS countries. As a result, several cooperation agreements have been signed during the forum.

‘Technologies of the Future: A Common Global Space or Every Nation for Itself?’ was the title of a session held on June 19, 2025, with the support of Alfa-Bank at this year’s St Petersburg International Economic Forum (SPIEF-2025). The discussion featured HSE University Rector Nikita Anisimov and was moderated by journalist, TV presenter, and public figure Ksenia Sobchak.

Researchers at HSE University and the AIRI Institute have proposed a method for quickly fine-tuning neural networks. Their approach involves processing data in groups and then optimally shuffling these groups to improve their interactions. The method outperforms alternatives in image generation and analysis, as well as in fine-tuning text models, all while requiring less memory and training time. The results have been presented at the NeurIPS 2024 Conference.

At the dawn of the 21st century, humans are increasingly becoming not just observers, but active participants in the technological revolution. Among the breakthroughs with the potential to change the lives of millions, brain–computer interfaces (BCIs)—systems that connect the brain to external devices—hold a special place. These technologies were the focal point of the spring International School ‘A New Generation of Neurointerfaces,’ which took place at HSE University.