Dr. Naoufel Werghi
Prof. naoufel werghi Professor Computer Science

Contact Information
naoufel.werghi@ku.ac.ae

Biography

Prof. Naoufel Werghi received his Habilitation and Ph.D. in Computer Vision from the University of Strasbourg. He has been a Research Fellow in the Division of Informatics at the University of Edinburgh, and a Lecturer in the Department of Computer Sciences at the University of Glasgow. Currently, he is a Full Professor at the Electrical Engineering and Computer Science Department in Khalifa University. He has been a Visiting Professor at the University of Louisville, the University of Florence, the University of Lille, the Children National Health System in Washington, the Korean Advanced and Institute of Sciences and Technology, and the University of Canberra.

He is the co-leader of the Artificial Intelligence and Data Analytics Theme in the Cyber-Physical Security System Center (C2PS), and project leader at Khalifa University Center for Autonomous Robotic System (KUCARS).

His research interests span computer vision and machine learning, where he has been leading several funded projects related to biometrics, medical imaging, remote sensing, surveillance, and intelligent systems. So far, he has secured 23 research grants and published more than 200 journal and conference papers, and received five best paper awards.

He has been a member of the organizing committee in many conferences, including the Midwest symposium on circuits and systems (2013) and the International Conference on Image Processing (2020).  He served as the vice-Chair of the IEEE Communications and Signal Processing UAE chapter in 2017, publication chair of the IEEE Int. Conference on Image Processing, 2020  & 2024, and   Chair of the IEEE PROGRESS workshop 2024.

He  Associate Editor of the IEEE Transactions on Circuits and Systems for Video Technology and the Eurasip  Journal for Image and Video Processing.


Education
  • PhD University of Strasbourg

Teaching
  • Computer vision
  • Artificial Intelligence
  • Deep Learning
  • Machine Learning

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Affiliated Centers, Groups & Labs

Research
Research Projects

Potential threats concealed within the baggage has become one of the prime security concern all over the world. Manual recognition of these threats is time-consuming and subject to human errors caused by fatigue due to intensive work schedules or less experienced operators. In this research, we aim to develop intelligent frameworks which can autonomously detect and recognize such threats, especially under extreme occlusion, clutter, and concealment.