Xiaolei Fang
Research Interests
Dr. Fang's research is centered on industrial data analytics, particularly for high-dimensional and big data applications across the energy, manufacturing, and service sectors. His work specifically targets the analytical, computational, and scalability challenges involved in creating statistical and optimization methodologies. These methodologies are designed to analyze massive, complex data structures for real-time asset management and optimization.
Methodologies: Data Science, Statistical Leanring, Machine Learning, Artificial Intelligence
Applications: Condition Monitoring, Anomaly Detection, Fault Root-Cause Diagnostics, Failure Time Prognostics, System Operation Decision-Making and Optimization
Employment
Aug. 2024 – Present, Associate Professor, Edward P. Fitts Department of Industrial and Systems Engineering, North Carolina State University, Raleigh, NC
Aug. 2018 – July 2024, Assistant Professor, Edward P. Fitts Department of Industrial and Systems Engineering, North Carolina State University, Raleigh, NC
May 2018 – Aug. 2018, Research Scientist, DecisionIQ, Atlanta, GA
Education
Georgia Institute of Technology, Atlanta, Georgia
University of Science and Technology Beijing, China
Honors and Awards
ISE Outstanding Research Award, Edward P. Fitts Department of Industrial and Systems Engineering, North Carolina State University, 2024
Finalist, QSR Best Student Paper Award, Quality, Statistics, and Reliability (QSR) Section of INFORMS, 2022 (Student: Chengyu Zhou)
Feature Article in ISE Magazine, 2021
Winner, QCRE Best Student Paper Award, Quality Control & Reliability Engineering (QCRE) Division of IISE, 2020 (Student: Cheoljoon Jeong)
Winner, Sigma Xi Best Ph.D. Thesis Award, Georgia Institute of Technology, 2019
Winner, Alice and John Jarvis Ph.D. Student Research Award, H. Milton Stewart School of Industrial and Systems Engineering (ISyE), Georgia Institute of Technology, 2018 (Awarded to one Ph.D. student in ISyE per year for outstanding research achievements)
Feature Article in ISE Magazine, 2017
Finalist, Best Student Paper Award, INFORMS Workshop on Data Mining & Decision Analytics, 2017
Winner, SAS Data Mining Best Paper Award, Data Mining Section of INFORMS, 2016
Finalist, QSR Best Refereed Paper Award, Quality, Statistics, and Reliability Section of INFORMS, 2016
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