معرفی
Yuantao Fan is an Associate Senior Lecturer at Halmstad University's School of Information Technology, specializing in artificial intelligence and machine learning applications for industrial systems. His academic work bridges theoretical research with practical implementations in predictive maintenance and equipment monitoring.
Dr. Fan's research focuses on Artificial Intelligence, Machine Learning, Anomaly Detection, and Data Mining, with particular emphasis on streaming data from real-world applications. His work spans equipment diagnosis and prognosis, predictive maintenance (PdM), and condition-based monitoring systems. His research integrates self-organizing models with expert knowledge to create robust diagnostic frameworks applicable to transportation systems and industrial equipment.
Analysis of Dr. Fan's publication record from 2013-2025 reveals consistent specialization in predictive maintenance for transportation systems, particularly bus fleets and heavy vehicles. His work demonstrates progression from basic fault detection methods to sophisticated hybrid approaches combining physics-based models with deep learning. Recent publications increasingly address explainability in predictive maintenance systems and applications in healthcare analytics.
Dr. Fan actively contributes to academic instruction as course responsible and examiner for Databases, Introduction to Linux and Python, and Linux administration system courses. He also teaches Artificial Intelligence, Data Mining, Perspectives on Computer Science and Engineering, Machine Learning for Predictive Maintenance, and AI Implementation courses.
His technical expertise spans multiple domains including automotive systems diagnostics, battery health monitoring, acoustic signal processing, and healthcare prediction models. Dr. Fan's work demonstrates strong industry collaboration, particularly with Volvo and city bus fleet operators, translating academic research into practical industrial applications.
