Department of Mathematical Modeling and Data Analysis
The Department of Mathematical Modeling and Data Analysis provides training for specialists in the F3 Computer Science program, with a strong focus on modern data analysis technologies, machine learning, and mathematical modeling of complex systems. Starting from the early years of study, the Department delivers fundamental courses in algorithm design, programming, mathematical modeling, and modern information technologies.
Head of the Department:
Volodymyr Mykhailovych Strukov, PhD (Engineering), Associate Professor.
Within the educational process, students study such disciplines as: algorithm design and programming, algorithms and data structures, object-oriented programming, operating systems, databases, distributed data processing, machine learning, deep learning, computer vision, neural networks, fuzzy logic and soft computing, modeling of complex systems, optimization methods and operations research, decision support systems, data mining, visual data analytics (Power BI, Tableau, Grafana), natural language processing, and large language models (LLMs).
The Department is focused on training specialists in the following areas:
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intelligent analysis of big data and data-driven decision-making;
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development and maintenance of architectures for big data collection, storage, and processing;
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creation of forecasting, classification, and complex systems modeling solutions;
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development and implementation of machine learning and artificial intelligence systems;
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design of databases and distributed computing systems;
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application of neural networks in applied and research tasks.
Graduates of the Department work in positions such as data analysts, data engineers, machine learning engineers, computer vision and NLP engineers, data architects, DevOps engineers, system and business analysts, as well as IT project managers.
The Department actively implements innovative approaches to education, including STEM education technologies, design-oriented learning (Design Thinking–based learning), and project-based learning in cooperation with leading IT companies.
Students have opportunities to undertake internships, work on real-world projects, develop individual educational pathways, and build their own professional roadmaps.
The main research areas of the Department include: data mining and machine learning; neuro-fuzzy systems and pattern recognition; mathematical modeling of complex systems and combinatorial structures; video and image data processing; modeling of processes in biosafety and epidemiological systems; steganographic and compression-based information security methods using artificial intelligence; and modeling of processes in plasma electronics systems and thermonuclear facilities.