Andrii Shkabrii

Andrii Shkabrii is a researcher affiliated with the Faculty of Computer Science, actively contributing to fields such as Data Mining, Machine Learning, and Clustering. His work bridges computational methods with archaeological data analysis, particularly in historical time studies.

• Education: MSc in Computer Science

Research Interests: Specializing in centroid-based deep clustering algorithms and non-redundant image clustering techniques, Shkabrii's work impacts both theoretical computer science and applied archaeology. He explores clustering quality metrics and domain expertise integration.

Publications (2023-2024): Recent work includes advancements in reclustering barriers (2024) and medieval glass bead analysis (2023), reflecting interdisciplinary applications of machine learning.