Kamran Paynabar

Kamran Paynabar is the Fouts Family Chair and Professor at the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Institute of Technology. He specializes in Engineering-Driven Statistical Modeling, Statistical Learning Methods for Big Data Analytics, and Quality Engineering, with applications in Manufacturing Systems and Healthcare.

• B.S. and M.Sc. in Industrial Engineering from Iran University of Science and Technology and Azad University (2002, 2004)
• M.A. in Statistics and Ph.D. in Operations Engineering from the University of Michigan (2010, 2012)

His research focuses on high-dimensional data analysis for system monitoring, diagnostics, and prognostics using semi-parametric and nonparametric approaches. Methodologies he develops address applications in automotive, aerospace, medical device manufacturing, and healthcare, including cardiac and orthopedic surgery analytics.

Dr. Paynabar’s publications from 2016–2025 highlight trends in anomaly detection, tensor analysis, Gaussian process modeling, and active learning applied to photovoltaic systems, additive manufacturing, and smart grids.

• INFORMS Data Mining Best Student Paper Award
• Best Application Paper Award from IIE Transactions
• Wilson Prize for Manufacturing Systems Research
• POMS Best Paper Award
• Georgia Tech CETL/BP Teaching Excellence Award

He has advised students like Xiaolei Fang (University of Florida), Hao Yan (Arizona State University), and Chitta Ranjan, with grants from the National Science Foundation (NSF). His work emphasizes interdisciplinary collaboration, bridging industrial engineering, machine learning, and system optimization.