You can stay in touch with all things SCL through our news feed or attending one of our upcoming events. SCL includes some of the world’s most experienced researchers in their fields who enjoy sharing their perspectives on a wide variety of topics. Our faculty is world-renowned and our students are intellectually curious and our alumni can be found around the globe in leadership positions within a wide variety of fields.
SCL reaches out to students, educators, businesses and the logistics community in an effort to increase exposure and accessibility to supply chain & logistics expertise through a variety of educational programs, partnership opportunities and outreach activities.
New ideas and new tools are born in the robust research environment supported by the Supply Chain & Logistics Institute. Solutions and improvements produced by researchers provide businesses with the high level of competitiveness that is critical to their success in the marketplace both at home and overseas.
Thousands of logistics and supply chain management professionals have advanced their knowledge—and their companies’ profitability—with the education they obtained through the courses and graduate degree programs offered through the Supply Chain & Logistics Institute and Stewart School of Industrial and Systems Engineering.
Kamran Paynabar is a Fouts Family Career Professor and Associate Professor in the Stewart School of Industrial and Systems Engineering at Georgia Tech.
Dr. Paynabar’s research interests comprise both applied and theoretical aspects of data mining and statistical modeling integrated with engineering knowledge. His current research focuses on the analysis of high-dimensional complex data including multi-stream signals, images, videos, point-clouds and network data, for system modeling, monitoring, diagnostics and prognostics using semi-parametric and nonparametric approaches. The generic methodologies he develops have been widely utilized in a variety of applications ranging from manufacturing including automotive, aerospace, medical device, and so forth, to healthcare applications including cardiac surgery and rotator cuff tear surgery.
Dr. Paynabar is the recipient of the 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 Quality and Reliability Engineering International Journal.
He 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. His teaching philosophy includes a structured method of teaching with clear communication, strong in-class interaction and engagement, and an imperative on a stress-free learning environment in an effort encourage intellectual curiosity. His overarching goal is to teach students how to think.
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.
Engineering-Driven Statistical Modeling
Statistical Learning Methods for Big Data Analytics
Class of 1969 Teaching Fellow (2013), Center for the Enhancement of Teaching and Learning (CETL), Georgia Institute of Technology -
“Thank a Teacher Certificates” for teaching ISYE 2028 (Fall 2012) and ISyE 3039 (Fall 2013), Center for the Enhancement of Teaching and Learning, Georgia Institute of Technology. 2012 -
Best Application Paper Award from IIE Transactions (2011), for paper “Characterization of Nonlinear Profiles Variations using Mixed-Effect Models and Wavelets,” IIE Transactions on Quality and Reliability Engineering, Vol. 43, 275–290. -
Best Student Paper Award in Data Mining Section of INFORMS (2011) for the paper; “Hierarchical Non-Negative Garrote for Group Variable Selection”. -
Richard C. Wilson Prize (2010) for The Best Student Paper in Manufacturing Systems; “Characterization of Nonlinear Profiles Variations using Mixed-Effect Models and Wavelets”. Industrial and Operations Engineering Department, University of Michigan. -