Dr. Nagi Gebraeel

Professor

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Biography

Nagi Gebraeel is a Georgia Power Professor at the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. He completed his Ph.D. in Industrial Engineering in 2003 and his M.S. in Industrial Engineering in 1998, both from Purdue University. His research focuses on Predictive Analytics, Machine Learning, and IoT-enabled maintenance and service logistics. He specializes in developing statistical learning algorithms for real-time diagnostics and prognostics of equipment, as well as optimization models for operational decision-making in IoT ecosystems. His work extends to developing cybersecurity algorithms for IoT-enabled critical assets against cyberattacks on Industrial Control Systems. His application domains include manufacturing and power generation, with recent interests in creating Self-Aware Deep Space Habitats for NASA. He leads the Predictive Analytics Intelligent Systems (PAIS) research group and manages the Analytics Prognostics Systems laboratory at Georgia Tech's Manufacturing Institute. Previously, he served as the Associate Director of Georgia Tech's Strategic Energy Institute from 2014 to 2019, promoting research initiatives at the intersection of Data Science and Energy applications.

Research Interests

Experience

Professor

2003-01-01 — Present

Georgia Institute of Technology • Atlanta, GA

Nagi Gebraeel serves as a Georgia Power Professor and leads multiple research initiatives in Predictive Analytics and Machine Learning.

Awards

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CAREER Award

2007-01-01
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SAE Aircraft Electrical Power System Recognition Award

2008-01-01
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IEEE-AUTOTESTCON Certificate

2006-01-01
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SAE Materials Modeling Testing Recognition Award

2006-01-01

Requirements for Georgia Institute of Technology

Doctorate Program
Requirements
GPA Requirement
Required:3.5
TOEFL
Listening
Required:19
Reading
Required:19
Writing
Required:19
Speaking
Required:19
Total
Required:100
IELTS
Listening
Required:6.5
Reading
Required:6.5
Writing
Required:5.5
Speaking
Required:6.5
Overall
Required:7.5
Prerequisites
Undergraduate degree in computer science or related field
Application Checklist
  • Online application
  • Official transcripts
  • Three letters of recommendation
  • Statement of Purpose
Specialization Notes

Department of Computer Science: GRE scores are optional for Fall 2026.