معرفی
Georg Peters is a Professor affiliated with the School of Arts and Humanities. His research spans data mining, machine learning, and educational technology, with a focus on rough sets, granular computing, and STEM education frameworks. He collaborates frequently with researchers like Richard Weber, Jan Seruga, and Tom Rueckert on interdisciplinary projects.
His work integrates computational methods with practical applications, such as credit scoring systems, dynamic data analysis tools, and educational platforms for mathematics and programming. A recurring theme is the development of frameworks that bridge theoretical computer science with real-world educational and analytical challenges.
Publications emphasize data-driven decision-making, clustering algorithms, and technology-enhanced learning. Recent articles explore probabilistic rough sets for finance, R-based educational environments, and dynamic granular clustering. No awards, students, or grants are mentioned in available sources.
