About
Jennifer Blair is a researcher at the University of Strathclyde's Department of Electronic And Electrical Engineering. Her work focuses on advancing analytics for nuclear asset lifecycle management, combining uncertainty quantification, transfer learning, and structural health monitoring techniques.
Her research interests span
- industrial fault diagnosis systems
- photometric stereo validation
- hybrid fault prognostics
- explainable data pipelines
- complex dependency modeling
- nuclear safety analytics
Recent publications highlight her contributions to uncertainty quantification in nuclear plant diagnostics (2024), photometric stereo data for structural validation (2024), and hybrid prognostic models addressing rotating plant uncertainty (2022). These works demonstrate cross-disciplinary applications in nuclear engineering, structural monitoring, and AI-driven diagnostics.
She collaborates with principal investigator Bruce Stephen and contributes to EPSRC-funded projects like "Supporting Analytics for Nuclear Asset Data Lifecycle" (2020-2025). Her doctoral thesis (2025) on nuclear asset lifecycle analytics further establishes her expertise in explainable data pipeline design.
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