BEN AYED Safa

Activités pédagogiques

• Disciplines : Apprentissage Automatique, Analyse de données, Informatique de Gestion, Réseaux & Télécommunication, Génie Electrique et Informatique Industrielle.
• Modules : Bloc IA, DATA avancée, Algorithmique, Systèmes d’exploitation, Programmation orientée objets, Réseaux informatiques, Développement web, Web dynamique, Outils logiciels mathématiques, Technologie de l’internet.
• Niveaux :  Ingénieurs informatique, Bachelor Maintenance, DUT 1ère et 2ème années, Licence 1ère année.

Programmes de recherche en cours

Collaboratrice dans le projet ANR SCOPES 2022-2025.

Publications

Synthèse (2017-2024)

• Revues internationales : 3
• Conférences internationales : 11
• Publications nationales : 2

Conférences internationales avec comité de lecture

• Ben Ayed, S., Ben Khalifa, M., & Ouchani, S. (2024). Modeling Distributed and Flexible PHM System based on the Belief Function Theory. In Internationale Conference of Artificial Intelligence Applications and Innovation (Springer).
• Hamza, R., & Ben Ayed, S. (2022, November). Supervised learning based approach for Turbofan engines failure prognosis within the belief function framework. In International Conference on Applied Computing.
• Ben Ayed, S., Elouedi, Z., & Lefevre., E. (2020). Managing uncertainty during CBR systems vocabulary maintenance using Relational Evidential C-Means. In: International Multi-Conference on: ”Organization of Knowledge and Advanced Technologies” (OCTA) (pp. 1-10).
• Ben Ayed, S., Elouedi, Z., & Lefevre, E. (2019, November). Exploiting prior knowledge for evaluating cbr systems using a coverage & constrained evidential clustering based model. In 16th International Conference on Applied Computing, AC'2019 (pp. 171-179).
• Ben Ayed, S., Elouedi, Z., & Lefevre., E. (2019). Toward the Evaluation of Case Base Maintenance Policies Under the Belief Function Theory. In: 15th European Conference on Symbolic and Quantitative Approaches with Uncertainty (ECSQARU) (pp. 113-124).
• Ben Ayed, S., Elouedi, Z., & Lefevre., E. (2019). CEVM: Constrained Evidential Vocabulary Maintenance Policy for CBR Systems. In: 32nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems (IEA/AIE) (pp. 579-592).
• Ben Ayed, S., Elouedi, Z., & Lefevre, E. (2018). Maintaining case knowledge vocabulary using a new Evidential Attribute Clustering method. In Data Science and Knowledge Engineering for Sensing Decision Support: Proceedings of the 13th International FLINS Conference (FLINS 2018) (pp. 347-354).
• Ben Ayed, S., Elouedi, Z., & Lefevre., E. (2018). CEC-Model: A new competence model for CBR systems based on the belief function theory. In: 26th International Conference on Case-Based Reasoning (ICCBR) (pp. 28-44).
• Ben Ayed, S., Elouedi, Z., & Lefevre., E. (2018). Exploiting domainexperts knowledge within an evidential process for case base maintenance. In: 5th International Conference on Belief Functions (BELIEF) (pp. 22-30).
• Ben Ayed, S., Elouedi, Z., & Lefevre., E. (2018). DETD: Dynamic policy for case base maintenance based on EK-NNclus algorithm and case Types Detection. In: 17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU) (pp. 370-382).
• Ben Ayed, S., Elouedi, Z., & Lefevre., E. (2017). ECTD: Evidential Clustering and case Types Detection for case base maintenance. In: 14th International Conference on Computer Systems and Applications (AICCSA) (pp. 1462- 1469).