Nagi Gebraeel

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Nagi Gebraeel is a Georgia Power Associate Professor in the Stewart School of Industrial & Systems Engineering at Georgia Tech.  He received his MS and PhD from Purdue University in 1998 and 2003, respectively.

Dr. Gebraeel's research interests lie at the intersection of sensor-based Predictive Analytics, Machine Learning, and Asset Management. His key focus is on developing next-generation machine learning tools specifically tailored for real-time equipment diagnostics and prognostics that enable subsequent operational and logistical decision-making. A significant component of his research deals with the scalability of these algorithms to Big Data settings that involve massive amounts of sensor data streams being generated from large fleets of equipment. From the standpoint of application domains, Dr. Gebraeel has a general interest in the energy industry with a focus on power generation, and the manufacturing industry with a focus on discrete and continuous manufacturing.

Dr. Gebraeel currently serves as an associate director at Georgia Tech's Strategic Energy Institute with the responsibility of identifying and promoting research initiatives and thought leadership at the intersection of Data Science and Energy. He is also the director of the Analytics and Prognostics Systems laboratory at Georgia Tech's Manufacturing Institute. Dr. Gebraeel was the former president of the Institute of Industrial Engineers (IIE) Quality and Reliability Engineering Division, and is currently a member of the Institute for Operations Research and the Management Sciences (INFORMS), The American Nuclear Society (ANS), and The American Institute of Aeronautics and Astronautics (AIAA).

 

Expertise:
  • Equipment Predictive Analytics
  • Machine Learning
  • Reliability and Maintainability Engineering
  • Power Generation Applications
  • Manufacturing Applications
The SAE Aircraft Electrical Power System Recognition Award for "Substantial Contribution to the Technical Program". 2008
The CAREER Award from the National Science Foundation. 2007
The SAE Materials Modeling and Testing Recognition Award for "Substantial Contribution to the Technical Program". 2006
The IEEE-AUTOTESTCON Certificate for "Substantial Contribution to the Technical Program". 2006