HSE University Strategic Development

Tag "Priority 2030"

Physicists at HSE University and FIAN Discover Way to 'Photograph' Sound for Testing Materials Used in 6G Communications

Physicists at HSE University and FIAN Discover Way to 'Photograph' Sound for Testing Materials Used in 6G Communications
Researchers at HSE University, in collaboration with colleagues from the Lebedev Physical Institute of the Russian Academy of Sciences (FIAN), have developed a method for rapidly determining how firmly a film is bonded to a substrate. This is important for the creation of ultrahigh-frequency acoustic filters, which are key components of next-generation 5G and 6G communications. For the first time, researchers have succeeded in measuring the lateral rigidity of the bond between a two-dimensional material film and a substrate in this way. The study results have been published in Applied Physics Letters.

Researchers Discover How Spelling Errors Slow Down Reading in Russian

Researchers Discover How Spelling Errors Slow Down Reading in Russian
Psycholinguists from the Centre for Language and Brain at HSE University–St Petersburg have shown that words that are frequently misspelled are processed more slowly by readers, even when presented with the correct spelling. The researchers confirmed this effect for the first time using Russian-language materials and found that response speed is most strongly linked to how confidently individuals can distinguish the correct spelling of a word from an incorrect one. The study has been published in The Mental Lexicon.

HSE Researchers Make Aldehydes Perform Dual Function

HSE Researchers Make Aldehydes Perform Dual Function
Chemists from HSE University have discovered a way to carry out a reductive addition reaction without using an external reducing agent. Instead, the required 'resource' is supplied by the aldehyde itself, one of the reaction participants. This approach helps prevent unwanted side reactions, reduces toxicity, and simplifies the production and synthesis of organic molecules, including those used in the manufacture of medicines. The study has been published in Journal of Catalysis.

HSE Scientists Develop Method to Compress Large Language Models Without Losing Quality

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.

HSE Study Reveals Imbalance in the Generative AI Market

HSE Study Reveals Imbalance in the Generative AI Market
Researchers at HSE University analysed how effectively the global generative artificial intelligence market converts investment into real revenue, concluding that AI is currently developing faster than it is paying off. The results have been published in the journal Foresight and STI Governance.

Teaching a Machine to Read the Past: HSE Develops Neural Network to Decipher Manuscripts

Manuscript of playwright Aleksandr Sukhovo-Kobylin
Diaries and letters are an invaluable resource for humanities scholars. But what can be done when the text is impossible to read? At the HSE Faculty of Humanities, this challenge has been translated into the language of mathematics: a team of philologists, historians, and machine learning specialists has created an information system that not only recognises illegible handwriting but also helps analyse archival content.

Scientists Develop Algorithm for Accurate Financial Time Series Forecasting

Scientists Develop Algorithm for Accurate Financial Time Series Forecasting
Researchers at the HSE Faculty of Computer Science benchmarked more than 200,000 model configurations for predicting financial asset prices and realised volatility, showing that performance can be improved by filtering out noise at specific frequencies in advance. This technique increased accuracy in 65% of cases. The authors also developed their own algorithm, which achieves accuracy comparable to that of the best models while requiring less computational power. The study has been published in Applied Soft Computing.

HSE and Nazarbayev University: Scientific and Educational Cooperation

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

‘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

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.