Kamran Paynabar Appointed to Fouts Family Early Career Professorship

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Georgia Tech’s Stewart School of Industrial and Systems Engineering announced that Assistant Professor Kamran Paynabar has been appointed to the Fouts Family Early Career Professorship.

“Kamran’s significant contributions to Stewart School and to the areas of statistical modeling and machine learning, particularly focusing on the analysis of high-dimensional streaming data for system monitoring, diagnosis, and prognosis, are reflected in his appointment to the Fouts Family Early Career Professorship,” said H. Milton and Carolyn J. Stewart School Chair and Professor Edwin Romeijn. “This appointment will provide Kamran with opportunities to enhance his career and further his research, which includes developing methodologies for a variety of applications ranging from manufacturing to health care.”

Paynabar’s research interests comprise both applied and theoretical aspects of data mining and statistical modeling integrated with engineering knowledge.

“I am honored to receive the Fouts Family Early Career Professorship, and thank the Fouts for their generous and continuous support of ISyE and early career faculty,” said Paynabar. “The Fouts Family Early Career Professorship will considerably help continue my research program and explore new research and education areas.”

Paynabar is the recipient of the INFORMS Data Mining Best Student Paper Award, the Best Application Paper Award from IISE Transactions, POMS Best Paper Award, INFORMS QSR Best Paper Award, and the Wilson Prize for the Best Student Paper in Manufacturing.

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 from the University of Michigan.


  • Workflow Status: Published
  • Created By: Shelley Wunder-Smith
  • Created: 04/12/2018
  • Modified By: Shelley Wunder-Smith
  • Modified: 04/12/2018


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