Speakers

Sourour Ammar

Place of Birth : Sfax, Tunisia
Position : Associate Professor, Higher Institute of Computer Science and Multimedia of Sfax, Tunisia
Field of study : Artificial Intelligence, Machine Learning, Deep Learning, and Computer Vision

Dr. Sourour Ammar is an internationally recognized researcher and Associate Professor at the Higher Institute of Computer Science and Multimedia of Sfax, Tunisia. She is also a key member of the SMARTS Laboratory at the Digital Research Center of Sfax. Dr. Ammar earned her Ph.D. in Machine Learning from the University of Nantes, France, in 2010, and has held prestigious research appointments, including as an R&D Engineer at INSA Rouen, France. Her research expertise spans machine learning, deep learning, computer vision, and ambient sensing, with practical applications in smart environments, healthcare, and document processing. She has authored numerous articles in high-impact journals and has presented her work at leading international conferences. Dr. Ammar has successfully led and contributed to major collaborations with institutions such as Orange Labs France, Sofrecom Tunisia, and the Blekinge Institute of Technology in Sweden, significantly advancing the global reach and societal impact of her research.

• Habilitation in Computer Systems Engineering (2024): University of Sfax, Tunisia
• Ph.D. in Computer Science (2010): University of Nantes, France
• Master in Computer Science (2007): University of Rouen, France
• Diploma in Computer Engineering (2006): ENIS, Tunisia
• Scientific Baccalaureate, specialty mathematics (2001): Tunisia

• Associate Professor, Higher Institute of Computer Science and Multimedia of Sfax (Since 2025)
• Assistant Professor, Digital Research Centre of Sfax (2017-2025)
• Assistant Professor, University of Monastir (2013-2017)
• Research and Teaching Assistant, University of Rouen (2011-2013)
• Research and Teaching Assistant, INSA Rouen (2010-2011)
• Research and Development Engineer, INSA Rouen (2007-2010)

• Artificial Intelligence / Machine Learning / Deep Learning
• Federated Learning
• Computer Vision
• Supervised and Unsupervised Learning