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وبینار امور بین الملل: Low Dimensional Learning from High Dimensional Data for System Modeling and Improvement
Low Dimensional Learning from High Dimensional Data for System Modeling and Improvement
با سخنرانی جناب آقای دکتر کامران پِینَبَر، 12 اسفند ماه 1399
Kamran Paynabar is Fouts Family Early Career Professor and Associate Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. 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. His research interests comprise both applied and methodological aspects of machine-learning and statistical modeling integrated with engineering principles for predictive modeling, system monitoring, diagnosis and prognosis. He is a recipient of the INFORMS Data Mining Best Paper Award, the Best Application Paper Award from IIE Transactions, the Best QSR Refereed Paper from INFORMS, and the Best Paper Award from POMS. He has been recognized with the Georgia Tech 2014 CETL/BP Junior Faculty Teaching Excellence Award and the Provost Teaching and Learning Fellowship. He served as the chair of Quality, Statistics, and Reliability of INFORMS, and the president of Quality Control and Reliability of IISE. He is Associate Editor for Technometrics, IEEE-TASE, INFORMS Journal of Computing, and INFORMS Journal of Data Science, a Department Editor for IISE-Transactions and a member of editorial board for Journal of Quality Technology.
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