Education and Qualifications
Diplomas
2017-2020: Ph.D, Aix-Marseille University, France.
2016-2020: Ph.D (joint), ENSI, University of Manouba, Tunisia.
2013-2016: Computer Sciences Engineering Degree, ENSI, University of Manouba, Tunisia.
2011-2013: First Cycle of University Studies, IPEIM, University of Monastir, Tunisia.
2011: Baccalaureate Degree, Bizerte-Tunisia.
Qualifications
Feb. 2022 : Qualification française aux fonctions de Maître de Conférences Section CNU 27 (Informatique)
Since March 2022 : Responsible of Data Science & Knowledge Engineering (DSKE) Department of LAboratoire de Recherche en Intelligence Artificielle (LARIA) UR22ES01, ENSI, University of Manouba.
Since October 2021 : Researcher in Computer Sciences at LARIA UR22ES01-ENSI
September 2019 - August 2022: Assistant Professor and Researcher in Computer Sciences at Polytech-AMU
September 2018 - January 2019: Part-time Lecturer (Enseignante Vacataire) in Computer Sciences at FSB, University of Carthage.
October 2016 - December 2020: PhD Student-Researcher in Computer Sciences at Aix Marseille University and University of Manouba.
January 2016 - September 2016: Engineer internship in Computer Sciences at COSMOS Lab., ENSI.
Track Program Committee Member of :
IEEE International Conference on Advanced Learning Technologies (ICALT), Track 4: Digital Game and Intelligent Toy Enhanced Learning.
International Workshop on Metaverse and Artificial Companions in Education and Society (MetaACES)
Reviewer for international conferences and journals :
IEEE ICALT 2019, 2020, 2021, 2022.
Artificial Intelligence Review, Springer (December 2021)
Education and Information Technologies, Springer (August 2021)
Entertainment Computing, Elsevier (May 2021)
Research Topics:
I am conducting my research in the field of Technology-Enhanced Learning (TEL), with an approach coming from the field of Artificial Intelligence, and more specifically from Data Science. My research works aim to contribute to the development and the innovation of the educational field by integrating digital learning/teaching tools into traditional classrooms as well as investigating several artificial intelligence methods and algorithms for improving users’ satisfaction (learners and teachers/instructors).
TEL systems: serious games, MOOCs, LMS, Blackboard-Learn, Moodle, educational chatbots
Learning Anaytics, Learning Dashboards, evaluation of learner experience
Affective Computing: emotion detection and recognition, engagement analysis, multimodal interaction
Artificial Intelligence: Data Mining, Machine/Deep Learning
Applications Domains: e-education, crisis and risk management
Teaching Activities
Disciplines : Computer science
Modalities : Lectures, TP, TD, Pedagogy by project (PBL)
Levels : L1, L2, L3, PEIP cycle, Engineering cycle, Alternation cycle, Master M1/M2.
Graduate courses for 3d level of the computer sciences engineering studies:
Unix Programming Environment
Algorithmics and Programming Language C
Games and Artificial Intelligence
Graduate courses for 1d and 2d level of the Cycle préparatoire-PeiP
Web Programming (HTML, CSS, JS)
Introduction to internet, Ms-Office (Excel), VBA
Data Bases (SQL)
Python
Undergraduate courses for 1d and 2d levels of the licence in computer sciences:
Introduction to OS & Data Communication Networks
Langages and automata Theory
Compilation Techniques
JAVA Programming
Modeling & conception OO: UML/MERISE
Graduate courses for the computer sciences Master studies (M1 & M2):
Advanced SQL
Mongo DB NoSQL
Git, GitHub, Gitlab
Introduction to Cybersecurity