Translation. Region: Russian Federation –
Source: Peter the Great St. Petersburg Polytechnic University –
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The "Analytics and Data Management in Data-Intensive Fields" (DAMDID/RCDL) conference, an interdisciplinary forum where researchers from various fields collaborate in data analysis, has opened at the Polytechnic University. DAMDID has been held since 1997. This year, the event is co-hosted for the first time by SPbPU and the Federal Research Center for Computer Science and Control of the Russian Academy of Sciences. Dmitry Zegzhda, Director of the Institute of Computer Science and Cybersecurity, chairs the conference's program committee.
From October 29 to 31, 2025, Peter the Great St. Petersburg Polytechnic University will host the XXVII International Conference "Data Analytics and Data Management in Data-Intensive Domains" (DAMDID/RCDL 2025).
The conference traditionally serves as a platform for the exchange of views between specialists from various fields of computer science. The main topic of DAMDID is data analysis and management. The conference is international, and its working languages are English and Russian. The opening ceremony took place on October 29.
Dmitry Zegzhda, Director of the Institute of Computer Science and Cybersecurity at the Polytechnic University, Professor, and Corresponding Member of the Russian Academy of Sciences, kicked off the conference and introduced guests to SPbPU, the Institute of Computer Science and Cybersecurity, and the institute's completed projects. Dmitry Petrovich particularly highlighted the Institute's research in data analysis and management. The institute's research focuses on, among other things, federated learning of artificial intelligence, monitoring and security of large-scale data-driven systems, and analyzing user behavior patterns using machine learning and big data analytics.
"This year, the conference is being held in 21 sections. Conference participants from various organizations around the world have submitted 108 papers to the organizing committee, which will be published in major scientific journals. We will hear and discuss 87 papers. These are significant numbers. This growth demonstrates the high interest in data management, and the diversity of the represented fields demonstrates the need to expand and deepen data analytics for companies across a wide range of fields. We will have an intensive work schedule for all three days, and I have no doubt it will be productive," said Dmitry Petrovich.
Viktor Zakharov, Scientific Secretary of the Federal Research Center "Informatics and Control" of the Russian Academy of Sciences, traced the evolution of the DAMDID conference in his speech. He also discussed which cities and research centers have hosted the conference previously. In 2022, the event was held at ITMO National Research University in St. Petersburg, in 2023 at HSE University in Moscow, and in 2024 in Nizhny Novgorod.
Natalia Tuchkova, Head of the Department of Mathematical Software Systems at the Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences, dedicated her presentation to the memory of Professor Vladimir Alekseevich Serebryakov. Serebryakov was one of the founders of the conference. Since the 2000s, Vladimir Alekseevich has conducted research related to the semantic analysis of scientific data and its integration within the Russian Academy of Sciences. His projects pioneered the implementation of a semantic data model for individuals and projects at scientific institutions. From the 2000s to the present, data on the RAS portal has been implemented using the semantic model developed under Vladimir Alekseevich's supervision. Few can cite examples of such longevity in the use of a domestic software product.
Vladimir Korenkov, Scientific Director of the M. G. Meshcheryakov Laboratory of Information Technologies at JINR, gave an overview of how digital technologies and data mining are applied in large-scale scientific projects.
On the first day, the conference continued with nine sections: machine learning methods, conceptual and ontological modeling, information security, etc.
Over the next few days, conference participants will discuss the development of a model for classifying MRI images by Alzheimer's disease stages using interpretive machine learning methods, data management in industrial-scale tasks using quantum technologies, multi-task deep learning in IoT networks for detecting anomalies and attacks, the scalability of the SoQoL disk DBMS, and more.
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