IT Research


In the IT curriculum, our teaching and research staff follow their own research, bringing together PhD students and student engineers. Our laboratories favor forward-thinking research and business-related research, with the support of companies and national organizations promoting research (ANR, OSEO etc.). This expertise also enables us to collaborate on numerous projects with businesses, universities, research organizations and engineering schools at the heart of the five centres of competitiveness: AsTech, Cap Digital, Moveo, Aero Space Valley and Systematic.

Modeling, conception and formal verification of complex systems based on components (distributed, mobile, real time, and hybrid) and applications of mecatronic, automobile, aeronautic and telecommunications systems.

A conception of systems based on functioning components

The techniques of component-based modeling are more and more common in the conception of distributed and responsive IT systems. They are based on the use of existing components,
software and material, patterns and framework conceptions which make a strong contribution to cost-reducing in terms of system development. We are studying the models, methods and processes of systems engineering which allow the conception of component-based systems which are sure to work, as well as the evaluation of their performance.

Metamodeling and integration of formal and semiformal models

In spite of their advantages, formal models put off users due to their notation and a lack of methodological support. In order to increase their use in industry, one solution is to combine them with semiformal methods. Our work focuses on theoretical studies related to collaboration between semiformal and formal models with an eye on the construction of complex structures. We plan to mix certain tools and existing formal models (B language, Simulink and RTL tools, EDA electronic conception tools) with semi-formal models (UML2/SysML), applying the engineering techniques of MDA/MDE models (Model-Driven Architecture / Model-Driven Engineering).

System diagnostics and automatic test generation

The automatic generation of texts, working from formal specifications, allows us to improve them.

Architecture of distributed and parallel systems

The performance and security of P2P, Grid Computing and Cloud Computing systems

Engineering of knowledge and applications

Semantic interoperability between heterogeneous systems

We use the ‘ontological’ approach, founded on a formalized representation of knowledge of layers, domains, systems and applications. In focusing our work on the formalism of modal description logics, architecture and specific languages can be used to model and manipulate ontologies (RDFS, OWL, etc.) aiming towards the semantic integration of heterogeneous systems.

The problems tackled within this framework are: :

  • The representation of knowledge and reasoning with an ontological basis
  • The indexation and semantic annotation of data and video streams
  • The semantic integration of data
  • The semantic integration of company processes: architecture composition (algebra of composition, dynamic, service-oriented composition, semantic coherence). The semantic composition of processes.

The architecture of semantic mediation

Reliable service composition in SOA (Service-Oriented Architecture)

The work is focused on web services, their indexation in terms of efficient research and the models for the composition of these services. Going further than the current standards of web services (WSDL, UDDI, SOAP, REST, etc.), the discovery of new services is based on ontologies (RDFS-S, OWL-S, etc).

Semantic web and social networks

  • Filtering and recommendation systems

  • Integration and semantic mediation

Models and tools for human learning

  • E-learning: architecture, norms and standards of LMS (Learning Management System)

  • Use in the world of IT for human learnin