Dear community,
On behalf of the Quality, Statistics, and Reliability (QSR) Section Council, we invite you to participate in the 2026 QSR Tutorial Series. The goal of the series is to provide QSR members and the general public with accessible, high-quality tutorials that expand their knowledge of emerging research areas and practical tools in quality, statistics, and reliability. The series consists of three tutorials that will take place via Zoom on February 27, March 27, and April 24 at 3 pm EST. The information of the first tutorial is below, and a flyer with the information of this and the other tutorials is attached. We look forward to seeing you there!
Data Science in Performance Quantification for Wind Turbine Generators
In 2022, INFORMS awarded the speaker and his team the Impact Prize "for their key roles in the development and deployment of a new paradigm for the accurate quantification of wind turbine output that has accelerated engineering innovation in this field." Performance and efficiency analysis is, in fact, a research subject deeply rooted in the INFORMS communities. But performance quantification of wind turbines in their power production efficiencies faces the challenges that the variable inputs cannot be compared through randomized controlled experiments. The speaker's team developed nonparametric data science methods and borrowed ideas from causal inference, resulting in a pipeline of three key components that produce a competent and accurate quantification method of small and moderate changes in wind turbine production efficiency. This 2-hour tutorial will walk you through the details of the development, including how to use the functions in a R package specifically developed for wind energy applications.
Dr. Yu Ding
Anderson-Interface Chair and Professor
H. Milton Stewart School of Industrial and Systems Engineering
Georgia Institute of Technology
Dr. Yu Ding is the Anderson-Interface Chair and Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. Prior to joining Georgia Tech, he was the Mike and Sugar Barnes Professor of Industrial and Systems Engineering at Texas A&M University. Dr. Ding's research is in the area of data and quality science and system informatics. He is the author of the CRC Press book, Data Science for Wind Energy, and a co-author of the Springer Nature book, Data Science for Nano Image Analysis. His research work is recognized by the 2019 IISE's Technical Innovation Award, 2022 INFORMS' Impact Prize, 2024 ASME's Blackall Machine Tool and Gage Award, and 2024 SME's S. M. Wu Research Implementation Award. Dr. Ding is the Editor-in-Chief of INFORMS Journal on Data Science and serves as IISE's Senior Vice President for International Operations. Dr. Ding served as the Editor-in-Chief of IISE Transactions for the term of 2021-2024 and Program Chair for IEEE CASE 2025. He is a Fellow of IISE, INFORMS, and ASME.
February 27, 2026 3:00pm (EST)
Zoom Link: https://kaist.zoom.us/j/87608794649
Kind regards,
The Organizing Committee:
Alan R. Vazquez, Tecnologico de Monterrey
Heeyoung Kim, KAIST
William Fisher, JMP
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Alan R. Vazquez
Assistant Professor
Tecnologico de Monterrey
Monterrey, Mexico
https://alanrvazquez.netlify.app/------------------------------