Madjid SADALLAH

Ph.D., Researcher - Engineer

Short Bio

I am a computer scientist specializing in the intersection of artificial intelligence and education (AIEd). My work focuses on both the theoretical foundations and practical applications within this field. I hold a PhD and a Magister degree in Computer Science from University Abderrahmane Mira, complemented by an Engineer’s degree in Computer Science from the University of Science and Technology USTHB.

Currently, I am a postdoctoral researcher at LIRIS within the TWEAK team. I contribute to the MOBILES project, which utilizes advanced analytics to understand and support the spatial practices of international students in France. In this role, I develop and apply AI-driven methods aimed at enhancing student integration and educational experiences.

Prior to my current position, I served as a research engineer at IMT Atlantique in Brest, France. There, I contributed to the development of innovative analytical tools and models for digital learning practices. Previously, I was a full-time researcher at the Algerian Research Center on Scientific and Technical Information (CERIST), where my work centered on data organization, learning technologies, educational data analysis, and the application of artificial intelligence to digital education. My research seeks to effectively bridge AI capabilities with educational needs, developing technology to make learning more accessible, effective, and personalized.

View Academic CV (French)

Research Interests

My research interests lie at the confluence of Learning Analytics, Educational Data Mining, and Artificial Intelligence in Education (AIEd). Key areas include:

  • Artificial Intelligence in Education (AIEd): Applying AI techniques to create personalized, adaptive, and optimized learning experiences.
  • Human-Computer Interaction (HCI): Designing and evaluating effective human-computer interactions within educational technologies.
  • Technology-Enhanced Learning (TEL): Leveraging technology to build more effective, engaging, and accessible learning environments.
  • Design and Co-Design of Learning Analytics Tools: Developing and refining tools for educational data analysis through user-centered and participatory design approaches.
  • Knowledge Engineering: Modeling, representing, and utilizing knowledge within intelligent educational systems.
  • Digital & Multimedia Document Reengineering: Structuring and transforming digital content and multimedia resources to enhance their pedagogical value and adaptability.
  • Hypermedia and Hypervideo Systems: Investigating and developing interactive hypermedia and hypervideo systems to enrich educational content delivery and exploration.