Nabila Tabassum

Working on the TransAIRail project at the University of South-Eastern Norway (USN), focusing on transformative AI solutions for predictive maintenance in railway systems. The research investigates how artificial intelligence, machine learning, Bayesian modelling, and knowledge-graph frameworks can improve the reliability, safety, and operational efficiency of railway power infrastructure. The project primarily focuses on critical converter-station assets such as transformers and circuit breakers, using real-world operational, SCADA, and sensor data collected in collaboration with Bane NOR. The work also explores interpretable and probabilistic AI approaches for fault detection, health-index modelling, and remaining useful life prediction under real-world industrial conditions such as noisy and imbalanced data. In addition, the project aims to support the transition from traditional maintenance strategies toward intelligent, data-driven, and condition-based maintenance frameworks for more sustainable railway operations.