Xiaolei Fang
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Associate Professor Address: 4177 Fitts-Woolard Hall, 915 Partners Way, Raleigh, NC 27607 |
Research Interests
Dr. Fang's research focuses on developing advanced statistical learning, deep learning, federated learning, generative AI, and optimization methods for forecasting and decision-making in industrial applications involving high-dimensional and large-scale data.
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
Ph.D. in Industrial Engineering
Minor: Machine Learning
Dissertation title: Predictive Analytics for Complex Engineering Systems Using High-Dimensional Signals
M.S. in Statistics
University of Science and Technology Beijing, China
B.S. in Mechanical Engineering
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