“I offer congratulations to Kamran for this career milestone,” said H. Milton and Carolyn J. Stewart School Chair and Professor Edwin Romeijn. “This promotion to associate professor reflects his achievements in the area of statistical modeling and machine learning, with a particular focus on the analysis of high-dimensional streaming data for system monitoring and prognosis.”

About Kamran Paynabar

Paynabar has developed generic methodologies that have been widely used in a variety of applications ranging from manufacturing including automotive, aerospace, medical devices, etc., to health care applications including cardiac surgery and rotator-cuff tear surgery.

He has received the INFORMS QSR Best Paper Award, POMS-Healthcare Best Paper Award, INFORMS Data Mining Best Student Paper Award, the Best Application Paper Award from IIE Transactions, and the Wilson Prize for the Best Student Paper in Manufacturing. His papers have been published or accepted for publication in Technometrics, IIE Transactions on Quality and Reliability Engineering, Journal of Quality Technology, ASME Transactions-Journal of Manufacturing Science and Engineering, and IEEE Transactions on Automation Science and Engineering.

Paynabar has a passion and enthusiasm for teaching and sharing knowledge with his students, and has been recognized with the Georgia Tech campus-level 2014 CETL/BP Junior Faculty Teaching Excellence Award.

He received his B.Sc. and M.Sc. in industrial engineering from Iran University of Science and Technology and Azad University in 2002 and 2004, respectively, and his Ph.D. in industrial and operations engineering from the University of Michigan in 2012. He also holds an M.A. in statistics (2010) from the University of Michigan.