Megascience, AI, and Supercomputers: HSE Expands Cooperation with JINR
Experts in computer technology from HSE University and the Joint Institute for Nuclear Research (JINR) discussed collaboration and joint projects at a meeting held at the Meshcheryakov Laboratory of Information Technologies (MLIT). HSE University was represented by Lev Shchur, Head of the Laboratory for Computational Physics at the HSE Tikhonov Moscow Institute of Electronics and Mathematics (HSE MIEM), as well as Denis Derkach and Fedor Ratnikov from the Laboratory of Methods for Big Data Analysis at the HSE Faculty of Computer Science.
One of HSE’s key initiatives at JINR will be the application of artificial intelligence and machine learning algorithms—developed by researchers at the HSE Faculty of Computer Science—to analyse experimental data generated at the NICA accelerator complex.
NICA (Nuclotron-based Ion Collider fAcility) is a proton and heavy-ion collider located in Dubna, designed to study the properties of dense baryonic matter. This accelerator complex enables scientists to recreate, in laboratory conditions, states of matter similar to those that existed in the first moments after the Big Bang.
Denis Derkach
‘NICA is an example of a megascience project—one of the largest international research facilities. Our participation reaffirms that HSE operates at the highest level of scientific research. Partnering with JINR, one of the world’s leading centres for particle physics, will significantly expand our research scope and attract talented young scientists to tackle pressing scientific challenges,’ said Denis Derkach, Director for Applied Research and Development of the HSE AI and Digital Science Institute and Head of the Laboratory of Methods for Big Data Analysis at the HSE Faculty of Computer Science.
According to Fedor Ratnikov, Leading Research Fellow at the HSE Laboratory of Methods for Big Data Analysis, both HSE and the Meshcheryakov Laboratory of Information Technologies (MLIT) are working towards the same goal—advancing cutting-edge physics research through state-of-the-art data processing and analysis methods.
Fedor Ratnikov
‘While MLIT is primarily focused on practical applications, our expertise lies in developing methodologies and approaches. This means we naturally complement each other in tackling this large-scale challenge,’ Fedor Ratnikov emphasised.
Another key area of collaboration will be distributed computing and the efficient utilisation of HSE’s cHARISMa HPC cluster and JINR’s Govorun supercomputer to solve complex problems in statistical physics.
Lev Shchur
‘We have long collaborated with our colleagues at the Joint Institute for Nuclear Research and were invited by Vladimir Korenkov, the Scientific Leader of the Meshcheryakov Laboratory of Information Technologies. We have developed unique algorithms capable of solving complex problems in statistical physics, which can also be applied to optimisation tasks. Our software solutions can fully utilise the power of supercomputers, which will undoubtedly benefit JINR’s scientific research, including in applied fields such as modern IT applications in agriculture and radiobiology. Additionally, we are also really interested in knowledge exchange on supercomputer optimisation and monitoring,’ shared Lev Shchur.
A vital aspect of the HSE–JINR partnership is the involvement of students in high-level research projects. The HSE Faculty of Computer Science and MIEM train specialists proficient in modern data analysis methodologies. However, hands-on experience with cutting-edge technologies can only be gained through participation in real-world projects. The collaboration with JINR provides students with the opportunity to engage in large-scale international megascience projects, such as NICA experiments at the Joint Institute for Nuclear Research.
As part of this partnership, researchers have agreed to hold a joint scientific session at the 11th International GRID'2025 Conference, scheduled for July 2025. During this session, participants will review and compare results from specific scientific tasks undertaken within the framework of HSE–JINR joint projects.
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