Technological Breakthrough: Research by AI and Digital Science Institute Recognised at AI Journey 2025
Researchers from the AI and Digital Science Institute (part of the HSE Faculty of Computer Science) presented cutting-edge AI studies, noted for their scientific novelty and practical relevance, at the AI Journey 2025 International Conference. A research project by Maxim Rakhuba, Head of the Laboratory for Matrix and Tensor Methods in Machine Learning, received the AI Leaders 2025 award. Aibek Alanov, Head of the Centre of Deep Learning and Bayesian Methods, was among the finalists.
Maxim Rakhuba received high praise from the scientific community and was awarded the national AI Leaders award for his outstanding contribution to the development of efficient modelling methods and big data processing. His project focuses on designing new approaches to accelerating and reducing the size of machine-learning models through the use of low-dimensional matrices and tensors. These techniques significantly boost the performance of deep-learning algorithms and reduce the resource demands of servers and data centres.
‘The approaches we are developing make it possible, for example, to reduce the number of parameters in modern neural networks, making them more accessible and efficient, which broadens the scope for their application,’ emphasised Maxim Rakhuba.
Aibek Alanov made it to the finals with his project ‘Efficient Control Mechanisms for Image and Audio Generative Models.’ His research focuses on adaptation and personalisation, editing real images without additional training, and improving low-latency speech quality for real-time applications.
As part of the Breakthrough Research and Technology session, Alexey Naumov, Director of the AI and Digital Science Institute, delivered a presentation entitled ‘Estimating Schrödinger Potentials.’ Sergey Samsonov, Head of the International Laboratory of Stochastic Algorithms and High-Dimensional Inference, presented his talk on ‘Training Methods for Generative Flow Networks.’
Vladimir Spokoiny, Academic Supervisor of the HSE Laboratory for Theoretical Foundations of AI Models, presented a study titled ‘Estimation and Inference of Deep Neural Networks.’ His talk addressed some of the most pressing challenges in modern machine learning, including predictive accuracy and the reliability of inference—issues of particular importance given the growing scale and complexity of AI applications.
Peter Lukianchenko, Head of the HSE Laboratory of Artificial Intelligence in Mathematical Finance, shared successful experience of applying AI within the financial services sector during the session ‘Artificial Intelligence in Customer Experience and Personalisation.’ His presentation focused on the development of a multi-agent simulator designed to recreate crisis events in financial markets.
Researchers from the institute also presented a number of important studies during the poster session, including scientific results obtained under a grant from the Third-Wave Artificial Intelligence Centre.
GAS: Improving Discretisation of Diffusion ODEs via Generalised Adversarial Solver.
Authors: Alexander Oganov, Ilya Bykov, Eva Neudachina, Mishan Aliev, Alexandr Tolmachev, Alexandr Sidorov, Alexandr Zuev, Andrey Okhotin, Denis Rakitin, Aibek Alanov.
Revisiting Non-Acyclic GFlowNets in Discrete Environments.
Authors: Nikita Morozov, Yan Maximov, Daniil Tiapkin, Sergey Samsonov.
A System for Automatic Multimodal Analysis of Emotions and Personality Traits Based on Semi-Supervised Cross-Domain Learning.
Authors: Elena Ryumina, Alexander Aksenov, Daria Koryakovskaya, Timur Abdulkadirov, Angelina Egorova, Sergey Fedchin, Alexander Zaburdaev, Dmitry Ryumin.
Evaluation of Tokeniser Adaptation Methods for Russian LLMs.
Authors: Georgy Andryushchenko, Maria Godunova, Vladimir Ivanov, Dmitry Kuzmin, Andrew Parinov, Anna Shchennikova, Elizaveta Zhemchuzhina.
OmicsFUSION: GenAI model for Omics Data.
Authors: Nazar Beknazarov, Artem Bashkatov, Maria Poptsova.
A delegation from the institute also attended other AI Journey 2025 events to support active engagement within the scientific community and to discuss new directions in the development of artificial intelligence technologies.
Anna Kozyreva
‘The participation of representatives from the AI and Digital Science Institute in AI Journey fosters the exchange of scientific ideas with leading experts, helps to establish partnerships, and encourages discussion of future growth areas. The expansion of the international scientific community is particularly valuable and helps to define more clearly the pathways for further progress in AI,’ noted Anna Kozyreva, Head of the institute’s Promotions and Communications Unit.
By maintaining a high level of research activity and continually advancing technological approaches, the HSE AI and Digital Science Institute reaffirms its leading position in the development of artificial intelligence and related scientific fields in Russia.
Timur Abdulkhadirov
Alexander Aksenov
Georgy Andryushchenko
Maria Godunova
Alexander Zuev
Vladimir Ivanov
Darya Koryakovskaya
Dmitry Kuzmin
Elena Ryumina
Alexander Sidorov
Anna Schennikova
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