Sorbonne Abu Dhabi Deepfake Study: Data Aug Boosts Generalization | AcademicJobs
Explore Sorbonne University Abu Dhabi's latest study on how data augmentation enhances deepfake video detection generalization, amid UAE's rising AI threats.
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Abdenour Hadid received his Doctor of Science in Technology degree in electrical and information engineering from the University of Oulu, Finland, in 2005. He is a Professor and Principal Investigator of a Chair on Artificial Intelligence at Sorbonne University of Abu Dhabi, where he is affiliated with the Sorbonne Center for Artificial Intelligence. His research focuses on physics-informed machine learning, forecasting, computer vision, deep learning, artificial intelligence, the internet of things, and personalized healthcare. Hadid has authored more than 400 papers in international conferences and journals. His work has garnered over 30,000 citations and an h-index of 61.
Hadid serves as a senior member of IEEE and as an Associate Editor of the journal Expert Systems. He received the Jan Koenderink Prize for fundamental contributions in computer vision. He held the Academy Research Fellow position from the Academy of Finland from 2013 to 2018 and received the Outstanding Visiting Professor award under the 100-Talent Program of Shaanxi Province, China. He has contributed to European research projects, one of which was selected as a Success Story by the European Commission. Key publications include works on face description with local binary patterns, face recognition, and face spoofing detection techniques.
Explore Sorbonne University Abu Dhabi's latest study on how data augmentation enhances deepfake video detection generalization, amid UAE's rising AI threats.