Research & Expertise

Mathematicians at HSE University in Nizhny Novgorod and the A.V. Gaponov-Grekhov Institute of Applied Physics of the Russian Academy of Sciences studied internal waves generated in the ocean after the explosive eruption of an underwater volcano. The researchers calculated how the waves vary depending on ocean depth and the radius of the explosion source. It turns out that the strongest wave in the first group does not arrive immediately, but after a significant delay. This data can help predict the consequences of eruptions and enable advance preparation for potential threats. The article has been published in Natural Hazards. The research was carried out with support from the Russian Science Foundation (link in Russian).

The application of mathematical models to the diagnosis and treatment of cardiovascular diseases contributes to the effective detection of patient predispositions and supports the selection of best treatment strategies. The use of mathematical models helps create new diagnostic tools and train neural networks to assist clinicians. Researchers from HSE University and colleagues from Saratov State Medical University are engaged in this work as part of the Mirror Laboratories project. In this interview, Natalya Stankevich, Senior Research Fellow at the International Laboratory of Dynamical Systems and Applications of the HSE Campus in Nizhny Novgorod, talks about what the collaboration has achieved so far.

In biomedical research, machine learning algorithms are often used to analyse data—for instance, to predict cancer recurrence. However, it is not always clear whether these algorithms are detecting meaningful patterns or merely fitting random noise in the data. Scientists from HSE University, IBCh RAS, and Moscow State University have developed a test that makes it possible to determine this distinction. It could become an important tool for verifying the reliability of algorithms in medicine and biology. The study has been published on arXiv.

Artificial intelligence is transforming every aspect of life, expanding both our capabilities and our boundaries. At the same time, it presents new challenges for humanity, including concerns about safety, ethics, and environmental sustainability. Today, each neural network leaves a significant carbon footprint. However, with responsible management, AI has the potential to benefit the planet and become a cornerstone of a sustainable future economy. Panos Pardalos, Academic Supervisor of the Laboratory of Algorithms and Technologies for Network Analysis at the HSE Campus in Nizhny Novgorod, emphasised this point as he addressed the XXV Yasin (April) International Academic Conference on Economic and Social Development.

The future is now more difficult for researchers to forecast, and events that are hard to predict are playing an increasingly significant role. But there is good news too: scientists are confident that humanity will adapt to any changes. This was the focus of discussion at the International Symposium ‘Foresight in a Rapidly Changing World,’ which took place as part of the 25th Yasin (April) International Academic Conference.

HSE University has launched a unique digital Repository of Socio-Economic Information, replacing the outdated platform for the unified archive of economic and sociological data. The update includes not only a refreshed interface and enhanced functionality but also a reimagined concept for the platform itself.

A study by researchers at the HSE Faculty of Economic Sciences and the Institute of Education have found that the number of academic papers published by research universities in international journals has tripled in the past eight years. Additionally, universities have developed more distinct specialisations. Thus, sectoral universities specialising in medical, pedagogical, technical, and other fields are twice as likely to admit students to target places. The study has been published in Vocation, Technology & Education.

The HSE Foresight Centre has been featured in a report by the United Nations Secretary-General as a successful example of a centralised approach to technology foresight. The document was prepared for the twenty-eighth session of the Commission on Science and Technology for Development, which is the United Nations’ focal point for technology foresight and technology assessment.

The Russian Science Foundation has completed its review of projects submitted for grants to support fundamental and exploratory research by teams, as well as 2022 grant winners applying for project extensions. In addition, interdisciplinary projects for fundamental and exploratory research awarded under the Presidential funding programme have been announced. Projects awarded under each of the three categories include submissions from researchers at all four campuses of HSE University.

Specialists at the HSE Faculty of Computer Science and Sber AI Lab have developed a geometric oversampling technique known as Simplicial SMOTE. Tests on various datasets have shown that it significantly improves classification performance. This technique is particularly valuable in scenarios where rare cases are crucial, such as fraud detection or the diagnosis of rare diseases. The study's results are available on ArXiv.org, an open-access archive, and will be presented at the International Conference on Knowledge Discovery and Data Mining (KDD) in summer 2025 in Toronto, Canada.