Laboratory members took part in the in-person module of the School of Applied Data Analysis at the Data Diving Academy.
Daria Maltseva and Irina Pavlova, members of the International Laboratory for Applied Network Research, served as experts in the in-person module of the All-Russian School of Applied Data Analysis, organized by the Data Diving Academy.
From December 4th to 6th, the in-person module of the all-Russian "School of Applied Data Analysis" project, an educational accelerator on artificial intelligence (AI) and Big Data, was held in Tomsk. The in-person part took place at the Institute for Big Data Analysis and Artificial Intelligence at Tomsk State University (TSU) and served as the starting point for a new cohort of the School, which then continued online until December 23rd.
The "School of Applied Data Analysis" is an intensive course for university teams, researchers, analysts, and NPO and foundation employees, focusing on the practical application of AI and data analysis without the need for advanced programming skills. In 2025, the School was supported by the Vladimir Potanin Charitable Foundation, and partners included the University Consortium of Big Data Researchers and the International Laboratory for Applied Network Research at the National Research University Higher School of Economics.
The in-person module program was structured around two parallel educational tracks – "AI Fundraiser" and "AI Researcher" – and included lectures, workshops, and hands-on experience with modern analytical platforms and large language models.
On December 3, lab members Daria Maltseva and Irina Pavlova held an in-person seminar, "Bibliometric Network Analysis for Studying Trends in Scientific Disciplines and Collaborations." This was the fourth in a series of ANR-Lab seminars for members of the Big Data Research Consortium in 2025. Participants gained practical skills in using bibliometric network analysis and the Biblioshiny program. This seminar served as the opening workshop for participants of the School of Applied Data Analysis.
Day 1, December 4: Introduction and start of track work
The official opening of the school began with an introductory lecture on big data and AI from Vyacheslav Goiko, Director of the Institute for Big Data Analysis and Artificial Intelligence at TSU. The program then divided into tracks.
In the "AI Fundraiser" track:
- Maria Bulygina, Director of the TSU Endowment Fund, spoke about the structure of endowments in Russia.
- TSU analysts Yulia Aleksandrova and Polina Basina presented data-driven fundraising strategies.
In the "AI Researcher" track:
- Yulia Aleksandrova introduced the audience to the breakthrough projects of the Big Data Research Consortium.
- Daria Maltseva and Irina Pavlova conducted a workshop on conducting AI literature reviews and generating hypotheses using large language models, and also demonstrated working with publications on the OpenAlex platform.
In the afternoon, Polina Basina gave a practical guide to data search and extraction, after which, together with Evgeny Petrov, Head of Text Analytics at the Tomsk State University Institute for Big Data Analysis and Artificial Intelligence, she began a series of workshops on using the PolyAnalyst analytics platform. The day concluded with Evgeny Lukyanchikov, Executive Director of Antiplagiat, delivering a lecture on the principles of transparent and ethical AI.
Day 2, December 5: A Dive into Generative AI and Analytics Tools
On the second day, participants mastered generative AI tools, content analysis, and data visualization methods.
In the "AI Fundraiser" track, Artem Feshchenko, Director of the Center for Technological and Research Support at the Tomsk State University Institute of Distance Learning, conducted a series of master classes, ranging from AI-powered value proposition design to empathic copywriting and fundraising campaign development.
In the "AI Researcher" track:
- School participants mastered natural language processing (NLP) and data visualization tools in PolyAnalyst and DataLens.
- Daria Maltseva and Irina Pavlova demonstrated content analysis methods using large language models.
As part of the evening program, Daria Dunaeva (RosNavyk project manager, Tomsk State University) and Irina Pavlova held a workshop on labor market analytics using the RosNavyk service.
Day 3, December 6: Project presentation
School participants worked on creating their own AI assistants and finalized analytical reports, visualizations, and project presentations.
Group work with experts during the school allowed participants to move from formulating a problem and hypotheses to creating a prototype digital solution.
The school marked another important milestone in the collaboration between the International Laboratory for Applied Network Research, the Institute for Big Data Analysis and Artificial Intelligence of Tomsk State University (TSU), and the University Consortium of Big Data Researchers.
