Chantal SAAD HAJJAR
أستاذ مشارك
Chef de département - informatique et communication
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مَعْهَد الهَنْدَسة العالِي في بَيروت
+961 (1) 421 000 تحويلة 3339 chantal.hajjar@usj.edu.lb
Graduating as an electrical engineer with a specialization in computer science from ESIB in 1993, I began my career as a system engineer at Integro, a French company specializing in software production, where I worked from 1993 to 1996. In 1997, I joined the Zahlé and Bekaa Campus (CZB) of USJ as a teaching assistant.In 2008, I obtained a Master's degree in modeling and computer simulation. From 2011 to 2014, I conducted doctoral research in computer engineering at Supélec, resulting in my doctoral thesis and my promotion to assistant professor. In 2016, I contributed to the creation of the ESIB branch at CZB and served as its coordinator until July 2022. From April 2021 to April 2022, I held the position of interim director of CZB.Since September 2022, I have been part of ESIB, where I have been appointed coordinator of the computer engineering and communications program. Additionally, since January 2023, I have held the position of deputy director of the ESIB preparatory classes.
محاور البحث
Artifical IntelligenceMachine LearningComputer VisionSelf-organzing maps
المنشورات والمداخلات
Kaok, N., Amer, L., Yaacoub, T., Bakouny, Y.,
Hajjar, C., Khatounian, F., Amara, J., Slim, R., Mansour, A. & Yaghi, C.
(2023). “Detecting Patient Readiness for Colonoscopy through Bowel Image
Analysis: A Machine Learning Approach”. International Conference on
Applications in Electronics Pervading Industry, Environment and Society.
Hajjar, C., Ghattas, G. Kharrat Sarkis, M. Chamoun,
Y. (2021). “Vine identification and characterization in goblet-trained
vineyards using remotely sensed images”. Remote Sensing, Vol 13, Issue 15.
Saad Hajjar, C., Hajjar, C. Esta, M., Ghorra
Chamoun Y. (2020). “Machine
learning methods for soil moisture prediction in vineyards using digital
images”. E3S Web of Conferences, 167 02004.C. Hajjar, H. Hamdan.
(2013). Interval Data Clustering using Self-Organizing Maps based on
Mahalanobis Distances, Neural Networks Vol 46, P.124-132C. Hajjar, H. Hamdan. (2012). Clustering of Interval Data using Self-Organizing Maps - Application to meteorological data, Applied Computational Intelligence in Engineering and Information Technology - Series Topics in Intelligent Engineering and Informatics - Springer Verlag, p. 135-146.
Anglais
French