Curriculum Vitae

Informations Générales

Pr. Youssouf EL ALLIOUI
Professeur-Chercheur en Informatique
Faculté Polydisciplinaire de Khouribga — Université Sultan Moulay Slimane (USMS), Maroc
y.elallioui@usms.ma · yelallioui@gmail.com
ORCID · Google Scholar · ResearchGate · LinkedIn

Formation

Doctorat en Informatique — 2012
Université Sidi Mohamed Ben Abdellah (USMBA), Fès, Maroc
En partenariat avec : LAAS-CNRS, Toulouse · CHU Hassan II, Fès
Thèse : Une approche de gestion de profils et de personnalisation des réponses neurologiques dans un environnement mobile (Projet TENEMO — Télé-NEuroScience Mobile)

Diplôme d’Études Supérieures Spécialisées (DESS) — Génie Informatique — 2007
Université Sidi Mohamed Ben Abdellah (USMBA), Fès, Maroc

Expérience Professionnelle

Enseignant-Chercheur — depuis février 2013
Université Sultan Moulay Slimane (USMS)
Faculté Polydisciplinaire de Khouribga — Département des Mathématiques et Informatique

• Enseignement de modules en Licence et Master (POO, Génie Logiciel, Web Dynamique)
• Encadrement de projets de fin d’études et mémoires de Master
• Activités de recherche en Machine Learning, EDM, Semantic Web
• Responsabilités administratives et coordination pédagogique

Enseignant Vacataire — 2013 – 2019
SUP’MANAGEMENT — École d’Ingénierie, Maroc

Enseignant Vacataire — février – mai 2012
IGA de Fès, Maroc

Formateur Certifié Java EE — septembre 2008 – juillet 2009
OFPPT — ISTA Al-Adarissa, Fès, Maroc

• Formation qualifiante : Concepteur Réalisateur Java EE

Enseignement

Compétences Techniques

Langages de programmation

• Python, Java, Java EE, PHP, SQL, R, JavaScript
• C/C++, C#, VB.Net, Objective-C
• XML, HTML/CSS, OWL, RDF, RDFS

Machine Learning & Intelligence Artificielle

• Scikit-learn, TensorFlow, Keras, PyTorch
• Hugging Face Transformers, NLTK, spaCy
• Weka, Jupyter Notebook

Semantic Web & Ontologies

• RDF, OWL, SPARQL, Protégé, Apache Jena

Bases de données

• MySQL, PostgreSQL, MongoDB, Oracle, SQL Server, MS Access

Analyse & Conception

• UML, Merise · Méthodes : RUP, cycle en V
• Design Patterns (GoF), Architecture MVC

Technologies & Frameworks

• Java EE (Servlet, JSP, EJB, JSF, Struts, Hibernate, RMI)
• ASP.Net, ADO.Net · Web Services (REST, SOAP)

Outils & Environnements

• Git, GitHub, Docker
• PyCharm, Eclipse, NetBeans, Visual Studio .Net
• LaTeX, Jekyll
• Rational Rose, PowerAMC Designer
• Protégé (ontology editor), Xcode (Apple Developer)

Serveurs & Réseaux

• Apache, Tomcat, JBoss, GlassFish, IIS
• TCP/IP, OSI, LAN/WAN/MAN

Publications

Integrating web usage mining for an automatic learner profile detection: A learning styles-based approach

O. El Aissaoui, Y. El Madani El Alami, L. Oughdir and Y. El Allioui, "Integrating web usage mining for an automatic learner profile detection: A learning styles-based approach," 2018 International Conference on Intelligent Systems and Computer Vision (ISCV), Fez, 2018, pp. 1-6, doi: 10.1109/ISACV.2018.8354021.

A fuzzy classification approach for learning style prediction based on web mining technique in e-learning environments

El Aissaoui, O., El Alami El Madani, Y., Oughdir, L. et al. A fuzzy classification approach for learning style prediction based on web mining technique in e-learning environments. Educ Inf Technol 24, 1943–1959 (2019). https://doi.org/10.1007/s10639-018-9820-5.

Combining supervised and unsupervised machine learning algorithms to predict the learners’ learning styles

AISSAOUI, O. EL, EL MADANI, Y. E. A., OUGHDIR, L., & ALLIOUI, Y. EL. (2019). Combining supervised and unsupervised machine learning algorithms to predict the learners’ learning styles. Procedia Computer Science, 148, 87–96. https://doi.org/10.1016/J.PROCS.2019.01.012.

Advanced prediction of learner’s profile based on Felder-Silverman learning styles using web usage mining approach and fuzzy c-means algorithm

Allioui, Y. El. (2019). Advanced prediction of learner’s profile based on Felder-Silverman learning styles using web usage mining approach and fuzzy c-means algorithm. International Journal of Computer Aided Engineering and Technology, 11(4/5), 495. https://doi.org/10.1504/IJCAET.2019.100447.

A Hybrid Machine Learning Approach to Predict Learning Styles in Adaptive E-Learning System

El Aissaoui O., El Madani El Alami Y., Oughdir L., El Allioui Y. (2019) A Hybrid Machine Learning Approach to Predict Learning Styles in Adaptive E-Learning System. In: Ezziyyani M. (eds) Advanced Intelligent Systems for Sustainable Development (AI2SD’2018). AI2SD 2018. Advances in Intelligent Systems and Computing, vol 915. Springer, Cham.

A new collaborative approach to solve the gray-sheep users problem in recommender systems

A. E. Fazziki, O. E. Aissaoui, Y. E. M. E. Alami, Y. E. Allioui and M. Benbrahim, "A new collaborative approach to solve the gray-sheep users problem in recommender systems," 2019 Third International Conference on Intelligent Computing in Data Sciences (ICDS), Marrakech, Morocco, 2019, pp. 1-4, doi: 10.1109/ICDS47004.2019.8942256.

A Multiple Linear Regression-Based Approach to Predict Student Performance

El Aissaoui O., El Alami El Madani Y., Oughdir L., Dakkak A., El Allioui Y. (2020) A Multiple Linear Regression-Based Approach to Predict Student Performance. In: Ezziyyani M. (eds) Advanced Intelligent Systems for Sustainable Development (AI2SD’2019). AI2SD 2019. Advances in Intelligent Systems and Computing, vol 1102. Springer, Cham.

Improving Collaborative Filtering Approach by Leveraging Opposite Users

El Fazziki A., El Madani El Alami Y., El Aissaoui O., El Allioui Y., Benbrahim M. (2020) Improving Collaborative Filtering Approach by Leveraging Opposite Users. In: Ezziyyani M. (eds) Advanced Intelligent Systems for Sustainable Development (AI2SD’2019). AI2SD 2019. Advances in Intelligent Systems and Computing, vol 1102. Springer, Cham.

Mining Learners’ Behaviors: An Approach Based on Educational Data Mining Techniques

El Aissaoui O., El Alami El Madani Y., Oughdir L., Dakkak A., El Allioui Y. (2020) Mining Learners’ Behaviors: An Approach Based on Educational Data Mining Techniques. In: Bhateja V., Satapathy S., Satori H. (eds) Embedded Systems and Artificial Intelligence. Advances in Intelligent Systems and Computing, vol 1076. Springer, Singapore

A Novel Collaborative Filtering Approach Based on the Opposite Neighbors’ Preferences

El Fazziki A., El Aissaoui O., El Madani El Alami Y., Benbrahim M., El Allioui Y. (2020) A Novel Collaborative Filtering Approach Based on the Opposite Neighbors’ Preferences. In: Bhateja V., Satapathy S., Satori H. (eds) Embedded Systems and Artificial Intelligence. Advances in Intelligent Systems and Computing, vol 1076. Springer, Singapore

Communications & Conférences

From E-learning 1.0 to E-learning 3.0 : A state of the art

May 26, 2015

Talk at International Conference on Big Data, Cloud and Applications (BDCA'2015), Tetuan, Morocco

Integrating web usage mining for an automatic learner profile detection: A learning styles-based approach

April 04, 2018

Talk at 2018 International Conference on Intelligent Systems and Computer Vision (ISCV), Fez, Morocco

A Hybrid Machine Learning Approach to Predict Learning Styles in Adaptive E-Learning System

July 14, 2018

Talk at International Conference on Advanced Intelligent Systems for Sustainable Development (AI2SD’2018), Tanger, Morocco

Combining supervised and unsupervised machine learning algorithms to predict the learners’ learning styles

October 05, 2018

Talk at The second International Conference On Intelligent Computing in Data Sciences (ICDS'2018), Fez, Morocco

A machine learning based approach to determine learners’ behaviors in adaptive educational systems

November 28, 2018

Talk at INTERNATIONAL CONFERENCE ON PEDAGOGICAL APPROACHES & E-LEARNING (APEL'2018), Fez, Morocco

A Novel Collaborative Filtering Approach Based on the Opposite Neighbors’ Preferences

May 03, 2019

Talk at ESAI'19: International Conference On Embedded Systems And Artificial Intelligence, Faculty of Medicine and Pharmacy Fez, Morocco, April 30-May 3, 2019

Mining Learners’ Behaviors: An Approach Based on Educational Data Mining Techniques

May 03, 2019

Talk at ESAI'19: International Conference On Embedded Systems And Artificial Intelligence, Faculty of Medicine and Pharmacy Fez, Morocco, April 30-May 3, 2019

A Multiple Linear Regression-Based Approach to Predict Student Performance

July 11, 2019

Talk at International Conference on Advanced Intelligent Systems for Sustainable Development (AI2SD’2019), Marrakech, Morocco

Improving Collaborative Filtering Approach by Leveraging Opposite Users

July 11, 2019

Talk at International Conference on Advanced Intelligent Systems for Sustainable Development (AI2SD’2019), Marrakech, Morocco

A new collaborative approach to solve the gray-sheep users problem in recommender systems

October 30, 2019

Talk at 2019 Third International Conference on Intelligent Computing in Data Sciences (ICDS), Marrakech, Morocco

Workshops :

• Big Data Training Workshop — ENSIAS, Rabat (mai 2016)
• Green ICT Workshop — ENSIAS, Rabat (mai 2016)
• IWTIE’16 — International Workshop on Technology Innovation and Entrepreneurship, ENSIAS, Rabat (mai 2016)

Activités Pédagogiques

09/2008 – 01/2011, Formation qualifiante, Concepteur Réalisateur Java EE

02/2012 – 05/2012, Environnement .NET, Cycle Ingénieur

03/2012 – 01/2019, Management de projets, Cycle Ingénieur

Unified Modeling Language (UML), Licence Pro., S6 (40 hours)

03/2014 – 01/2015, Formation continue, Master

Web Dynamique (PHP 5, MYSQL), Licence fondamentale, SMI, S6 (50 hours)

Object-oriented programming (OOP), Licence Pro., S6 (44 hours)

Responsabilités & Service Académique

• Coordonnateur de la filière SMI (Sciences Mathématiques et Informatique), USMS
• Chef de la Commission Scientifique chargée de la recherche, de la bibliothèque et des archives
• Membre du Collège du Département des Mathématiques et Informatique
• Membre des Commissions de Recrutement des postes d’enseignants-chercheurs
• Membre de comités de programme de conférences et workshops internationaux (AI2SD, ICDS, ESAI)
• Reviewer pour des revues et conférences internationales indexées

Affiliations & Profils Académiques

Dernière mise à jour : April 2026