Virtual Mozart, Venture Capital Bot, and Educational Video Generation: How AI is Used at HSE University
In mid-November, HSE University hosted a meetup where faculty, researchers, and administrators presented their projects and shared experiences with using AI technologies in education and research. The meeting was part of the continuing professional development programme 'Artificial Intelligence in Education and Research.'
The 'Artificial Intelligence in Education and Research' project supports the initiatives of university staff aiming to leverage advanced technologies to enhance the quality of education and scientific research. The project is carried out within the framework of the Priority 2030 Strategic Academic Leadership Programme.
Redesigning a Venture Capital Course Using AI Elements
Alexander Semenov, Associate Professor at the School of Finance, Faculty of Economics Sciences, shared his experience using artificial intelligence to redesign a course in Venture Capital. One of the primary goals of using AI was to enhance students' understanding of the financial investment market and innovative business practices.
Alexander Semenov
For this purpose, a virtual assistant was developed based on the psychologist chatbot Anna that interacts with students, helping them answer challenging questions and become more psychologically prepared to engage with investors. The use of this virtual assistant has enhanced the quality of student training and introduced new tools for discussing the psychological aspects of entrepreneurship.
AI Simulacra for a Figital Art Course
Evgeniya Evpak, Research Assistant at the HSE ISSEK Laboratory for Economics of Innovation and visiting lecturer at the HSE Art and Design School, presented a project centred on integrating AI simulacra into a course on figital art.
Evgeniya Evpak
The project’s main idea was to create virtual avatars of historical figures, such as Plato, Jean Baudrillard, and Wolfgang Amadeus Mozart, to facilitate educational dialogues with students. These avatars were created using the Hedra and GigaChat neural networks, enabling the integration of gamification elements into the educational process and the creation of an interactive environment for studying figital art and its theoretical foundations. This approach will not only save time in creating educational video materials but also make learning more engaging for students.
AI Tools for Teaching Foreign Languages
Natalia Ryapina, Senior Lecturer at the School of Foreign Languages, HSE Campus in Perm, shared her experience using AI to teach foreign languages.
Natalia Ryapina
The main focus was on using multimodal AI tools, such as Gamma and EdrawMind, which help adapt educational materials and contribute to their comprehension by students. Generating content in various formats (video, audio, text) using artificial intelligence caters to students with different learning styles, increasing their engagement in the educational process and helping them immerse themselves more deeply in the material.
Integration of AI in Educational Activities
Ksenia Fimina, Senior Lecturer at the HSE School of Applied Mathematics, demonstrated how artificial intelligence can optimise the creation of educational materials.
Ksenia Fimina
In her work, she uses AI tools like Narakeet and Invideo AI, which reduce the time required to create presentation-quality videos by more than tenfold. AI tools offer teachers a wide range of ready-made templates and ideas for visually presenting lecture material, helping make the educational process more engaging and accessible for students. Ksenia Fimina also uses neural network technologies in developing a digital assistant for medical researchers as part of the Smart Medicine project.
Using AI to Examine the Narrative Structure of a Text
Marharyta Fabrykant, Senior Research Fellow at the Expert Institute's Laboratory for Comparative Studies in Mass Consciousness, presented the results of a study on using AI tools to analyse the emotional tone of a text and examine its narrative structure.
Marharyta Fabrykant
The project employed emotional dynamics analysis using the NLTK library to study the ancient epic of Gilgamesh. The study revealed patterns in the emotional structure of the text, confirming hypotheses about the rise and fall of emotional intensity at key moments of the narrative. Marharyta Fabrykant's project demonstrates the potential of using AI technologies for objective analysis of complex texts, which is highly significant for conducting humanities research.
The ‘Artificial Intelligence in Education and Research’ is a continuing professional development programme implemented by the HSE Faculty of Computer Sciences' Continuing Education Centre and the HSE Centre for Staff Continuing Professional Development.
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Biologists Discover 'Molecular Fingerprint' of Preeclampsia
Researchers at HSE University employed a new method to model hypoxia in placental cells during pregnancies complicated by preeclampsia and identified molecular markers of tissue hypoxia. Since hypoxia is one of the key mechanisms underlying preeclampsia, these findings are important for a more accurate and timely diagnosis of the disease and for the development of effective treatment methods. The paper has been published in Placenta.
‘Hedgehog’ Versus ‘Relatives’: Researchers Measure How the Brain Responds to Unexpected Words During Natural Speech
Russian neurophysiologists, including researchers from HSE University, have demonstrated the feasibility of using event-related fields (ERFs) to study brain activity during natural speech perception. The researchers showed that this approach can be applied not only to individual words but also to continuous speech. Their findings indicate that words whose meanings differ significantly from the preceding context require longer processing times. The study also reveals that the brain processes function words in two stages: first, it identifies their grammatical role and then uses this information to predict the next word. The study has been published in Frontiers in Human Neuroscience.
Scientists Develop Algorithm for More Reliable Processors in Data Centres
Researchers from HSE MIEM and Samara University have developed the LRF-3D algorithm to automatically bypass idle nodes in three-dimensional networks-on-chip. Thanks to its hierarchical architecture, the algorithm outperforms existing solutions in both speed and path accuracy, improving processor reliability for use in data centres, supercomputers, and AI computing. The source code and test results are publicly available.
Researchers Develop Method for Direct Generation of Regulatory DNA
Researchers at HSE University have developed a model for generating promoters and enhancers—DNA sequences that regulate gene activity. The model works directly with DNA nucleotides, without first transforming them into a continuous numerical representation. This solution could be useful for applications in synthetic biology and gene therapy. The study results were presented at the ICLR 2026 Workshop ‘Generative AI in Genomics (Gen^2): Barriers and Frontiers.’
Researchers at HSE University and Sber Train Neural Networks to Better Predict User Preferences
The HSE FCS AI and Digital Science Institute and Sber have introduced a new architecture for recommendation systems that combines two classes of models, enabling algorithms to better predict users’ interests and needs. A preprint of the paper has been published on arxiv.org and presented at Urban ML.
Physicists Discover What Happens Inside a Stable Vortex
Large vortices with characteristic spiral arms are often observed in the atmosphere and the ocean. Physicists from HSE University have explained how these structures form and why they retain their shape. The researchers found that velocities at points located along the same vortex arc remain correlated even over long distances. At the same time, this correlation weakens rapidly with increasing distance from the vortex centre. These differences help explain the formation of spiral arms and may improve models of atmospheric and oceanic currents. The findings have been published in Physical Review Fluids.
‘The Peak of Stupidity’ and ‘The Valley of Despair’: HSE Economists Propose an Explanation for the Dunning–Kruger Effect
The Dunning–Kruger effect, which describes a sharp surge in self-confidence among beginners followed by an equally rapid decline as they gain experience, can be explained by the nature of the learning process and the acquisition of new knowledge. This conclusion was reached by Andrey Vorchik of the HSE Faculty of Economic Sciences together with independent researcher Murat Mamyshev. They developed a mathematical model of learning and demonstrated how subjective confidence is formed and changes as knowledge accumulates, as well as how teachers can reduce the ‘valley of despair’ experienced by learners.
Toffee and Risk: Scientists Discover Why People Who Crave Sweets Make More Impulsive Choices
Having a sweet tooth may be linked not only to eating habits but also to the way people make decisions. Researchers at HSE University have found that people with a preference for sweet foods tend to behave more impulsively—not because they want immediate rewards, but because they are less willing to tolerate uncertainty. These findings may help improve treatments for addiction. The study findings have been published in Frontiers in Psychology.
Physicists Find a Way to Model Ion Parameters in Plasma in Seconds
Researchers from HSE University and the Moscow Institute of Physics and Technology (MIPT) have developed a set of simple analytical methods for calculating the properties of heavy ions in helium under the influence of a strong electric field. The new approach speeds up calculations of ion mobility and ion–molecule reaction rates by thousands of times while maintaining sufficient accuracy for plasma jet modelling. The findings have been published in the journal Physica Scripta.
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.