Bio

Xiaolei Fang‘s research interests lie in industrial data analytics for High-Dimensional and Big Data applications in the energy, manufacturing and service sectors. Specifically, he focuses on addressing analytical, computational, and scalability challenges associated with the development of statistical and optimization methodologies for analyzing massive amounts of complex data structures for real-time asset management and optimization.

Methodologies:

• Data science
• Machine learning

Applications:

• System performance assessment and optimization
• System anomalies detection
• Fault root causes diagnostics
• Remaining useful lifetime prediction
• Decision-making and control