Guanzhou Wei

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Guanzhou Wei joined the IMSE department at Iowa State University in fall 2025 as an assistant professor. His research focuses on statistics and data science, with an emphasis on statistical learning for complex spatio-temporal processes and their applications in energy and environmental systems.

Education

• Ph.D. in Industrial Engineering, 2025, Georgia Institute of Technology
• Master in Industrial Engineering, 2019, Tianjin University
• Bachelor in Industrial Engineering, 2016, Jilin University

Fall 2025 New Faculty Spotlight:

What makes you most excited to join the Cyclone Engineering community here at Iowa State?

I am most excited to join a supportive and collaborative community at Iowa State University that values applied and interdisciplinary research. The Cyclone Engineering culture of working across fields offers the ideal environment for me to advance my data science research and collaborate with colleagues and students to create solutions that make a real difference.

Describe a moment that makes you particularly proud of your career path in educating tomorrow’s engineers.

I am particularly proud when my research is published in leading journals or when I am invited to serve as a reviewer for academic journals. These moments show that my work contributes to advancing both theory and practice, while also helping to build the knowledge foundation that will guide the education of tomorrow’s engineers.

How do you hope your teaching and/or research discoveries impact the world?

I hope my research advances data-driven methods and data analytics through high-quality, world-class work that contributes new theoretical and methodological insights. By building stronger analytical foundations to understand complex natural spatio-temporal processes, I aim to support practical solutions that help society and communities enhance safety and resilience in energy and environmental systems.

What kind of classroom and teaching experience do you look forward to creating at Iowa State?

My teaching will emphasize a strong foundation in statistics and stochastic models, balanced with opportunities for students to apply these tools to real-world problems. Most importantly, I want to foster a supportive atmosphere where students feel encouraged to ask questions, collaborate with peers, and develop the confidence to become innovative and responsible engineers.

Publications

https://scholar.google.com/citations?user=MbnSv3kAAAAJ&hl=en&oi=ao

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