Rong Pan
Professor, School of Computing and Augmented Intelligence
Rong Pan is a professor of industrial engineering and data science in the School of Computing and Augmented Intelligence at Arizona State University and a Fellow of the American Society for Quality. He serves as program chair of the Data Science, Analytics and Engineering program and previously led ASU’s Industrial Engineering and Engineering Management programs. Before joining ASU in 2006, he was an assistant professor at the University of Texas at El Paso and held industrial positions in quality engineering.
Professor Pan’s research integrates statistical modeling, data analytics, and artificial intelligence to improve the reliability and performance of complex engineering systems. His foundational contributions span quality and reliability engineering, accelerated life and degradation testing, design of experiments, Bayesian modeling, time-series analysis and system reliability. His recent work extends these foundations to causal discovery, graph learning, data quality and diversity, change-point detection, knowledge graphs, trustworthy AI, and human-AI systems. He also applies digital twins and data-driven methods to multistage advanced manufacturing, where decisions and quality outcomes are coupled across processes. His research has been supported by the National Science Foundation, Department of Energy, Department of Defense, Air Force Research Laboratory, and Los Alamos National Laboratory.
Pan is an editor of the Journal of Quality Technology and previously served as chair of the ASQ Reliability and Risk Division. His honors include the IISE William A. Golomski Award, the Society of Reliability Engineers Stan Ofsthun Award, the American Statistical Association’s Statistics in Physical and Engineering Sciences Award and multiple Quality Engineering Best Reliability Paper Awards. He coauthored Design of Experiments for Reliability Achievement and has mentored students whose research received first-place RAMS student paper awards. Pan earned his doctorate in industrial engineering, with a minor in statistics, from Pennsylvania State University, a master’s degree from the joint FAMU-FSU College of Engineering and a bachelor’s degree from Shanghai Jiao Tong University.
Ready to mentor
Agentic AI, including harness engineering and multi-agent system design and optimization; data science, including topological data analysis, time series forecasting.