Tag "research projects"

Until September 14, 2025, the Russian capital is hosting a large-scale forum-festival called ‘Territory of the Future: Moscow 2030’ —a space for technology, science, and innovation. This event showcases cutting-edge developments in medicine, astronautics, and the digital economy. HSE Art and Design School is participating in the festival with two graduate projects in Product and Industrial Design.

This year, the European AI Conference (ECAI 2025) accepted an article titled ‘Multi-Agent Path Finding for Large Agents is Intractable’  by Artem Agafonov, a second-year student of the Applied Mathematics and Information Science Bachelor’s programme at HSE University’s Faculty of Computer Science. The work was co-authored by Konstantin Yakovlev, Head of the Joint Department with Intelligent Technologies of System Analysis and Management at the Federal Research Centre ‘Informatics and Management’ of the RAS and Associate Professor at the Faculty of Applied Sciences. In the interview, Artem Agafonov explained how he came up with the idea for the article and how he was able to present it at an A-level conference.

Mathematicians around the world share a common language and continue to collaborate despite the challenges of recent years. The hub of mathematical networking has been shifting to China, where scientists from various countries meet at conferences and other academic events. Partnerships with leading Chinese universities offer promising opportunities to strengthen existing ties and forge new ones. In this interview with the HSE News Service, Valery Gritsenko, Head of the HSE International Laboratory for Mirror Symmetry and Automorphic Forms, discusses this and other topics, including what AI is and why the state should engage with mathematicians.

In July, a team from the HSE Centre for Language and Brain, in collaboration with the Centre for the Study, Preservation, and Development of Native Languages of the Academy of Sciences of the Republic of Sakha (Yakutia), conducted the first-ever neurolinguistic expedition to the village of Churapcha to study reading in the Yakut language using electroencephalography (EEG). For the first time, EEG data from 43 adults and behavioural data from 40 children was collected during the two-week expedition.

Scientists at the HSE Centre for Language and Brain have identified key factors that increase the effectiveness of mobile and computer-based applications for aphasia rehabilitation. These key factors include automated feedback, a variety of tasks within the application, extended treatment duration, and ongoing interaction between the user and the clinician. The article has been published in NeuroRehabilitation.

Researchers from the International Laboratory of Dynamical Systems and Applications at the HSE Campus in Nizhny Novgorod have developed a theory that enables a mathematical proof of robust chaotic dynamics in networks of interacting elements. This research opens up new possibilities for exploring complex dynamical processes in neuroscience, biology, medicine, chemistry, optics, and other fields. The study findings have been accepted for publication in Physical Review Letters, a leading international journal. The findings are available on arXiv.org.

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).

Scientists from Yandex, HSE University, MIT, KAUST, and ISTA have made a breakthrough in optimising LLMs. Yandex Research, in collaboration with leading science and technology universities, has developed a method for rapidly compressing large language models (LLMs) without compromising quality. Now, a smartphone or laptop is enough to work with LLMs—there's no need for expensive servers or high-powered GPUs.

Researchers at the HSE Faculty of Computer Science have developed a new approach to modelling data storage systems based on generative machine learning models. This approach makes it possible to accurately predict the key performance characteristics of such systems under various conditions. Results have been published in the IEEE Access journal.

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.