Dr. Yu Ding is the Anderson-Interface Chair and Professor in the H. Milton School of Industrial and Systems Engineering at Georgia Tech. Prior to joining Georgia Tech in 2023, he was the Mike and Sugar Barnes Professor of Industrial and Systems Engineering at Texas A&M University and served as Associate Director for Research Engagement of Texas A&M Institute of Data Science. Dr. Ding's research is in the area of data and quality science. He received the 2019 IISE Technical Innovation Award and 2022 INFORMS Impact Prize for his data science innovations impacting wind energy applications. Dr. Ding is a Fellow of IISE and ASME. He has served as editor or associate editor for several major engineering data science journals, including as the 14th Editor in Chief of IISE Transactions, for the term of 2021-2024.

• Chapter 1 Introduction Part I Wind Field AnalysisChapter 2 A Single Time Series Model Chapter 3 SpatiotemporalChapter 4 RegimeswitchingPart II Wind Turbine Performance AnalysisChapter 5 Power Curve Modeling and Analysis Chapter 6 Production Efficiency Analysis Chapter 7 Quantification of Turbine Upgrade Chapter 8 Wake Effect Analysis Chapter 9 Overview of Turbine Maintenance Optimization Chapter 10 Extreme Load Analysis Chapter 11 Computer Simulator Based Load Analysis Chapter 12 Anomaly Detection and Fault Diagnosis

"This is the first book that focuses on the data science methodologies and their applications in a growing field, wind energy. It is well-organized and well-written. It will enhance the knowledge base of data science and its applications in the wind energy field."-- Elsayed A. Elsayed, Professor, Rutgers University