Teams
IRCCyN Teams
The main topics addressed by the research team ACSED concern the study of discrete-event systems and hybrid systems, for the design of industrial processes, and synthesis of control and supervision systems. The motivations and applications are in production system and their online managing and control.
Formal methods and discrete-event based simulation are used as complementary approaches for mathematical modelling and analysis.
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ADTS (Analysis and Decision in Signal Processing)
The problems which interest "Analysis and Decision in Signal Processing" (ADTS) team relate to the extraction of characteristic information starting from a disturbed signal, at ends of decision (classification, assistance with the diagnosis, detection of breakdowns, and change of operation...)
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The main objective of the Control team is to analyze and to solve control problems for dynamical systems that are described by mathematical models of various natures.
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MCM (Design Methods in Mechanics)
The goal of the MCM team is to develop new methods for the creation of new products and for the optimization of products.
The main application areas are machine-tools, robotics, aeronautics, shipbuilding, automotive industry and musical acoustics
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IREENA Teams
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LINA Teams
ASCOLA (ASpect and COmposition LAnguages)
ASCOLA addresses the general problem of structuring and evolving software by developing concepts, languages, implementations and tools for building software architectures based on components and aspects. Its long term goal is the development of new abstractions for the programming of software architectures, their representation in terms of expressive programming languages and their correct and efficient implementation.
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Today's hard problems in data management go well beyond the traditional context of Database Management Systems (DBMS). These problems stem from significant evolutions of data, systems and applications. First, data have become much richer and more complex in formats (e.g., multimedia objects), structures (e.g., semi-structured documents), content e.g., incomplete or imprecise data), size (e.g., very large volumes), and associated semantics (e.g., metadata, code). The management of such data makes it hard to develop data-intensive applications and creates hard performance problems. Secondly, data management systems need to scale up to support large-distributed systems (such as the Internet or cluster systems) and deal with both fixed and mobile clients. In a highly distributed context, data sources are typically in high number, autonomous and heterogeneous, thereby making data integration difficult. Third, this combined evolution of data and systems gives rise to new, typically complex, applications with ubiquitous, on-line data access: virtual libraries, virtual stores, global catalogs, services for personal content management, services for mobile data management, etc.
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ATLAS-GRIM address research issues dealing with data processing and management: summarization, clustering, indexing and retrieval, querying, classification.
Team focuses on specific data types or representations : data is represented by parametric models of data sets (specifically fuzzy sets or probabilistic models), or spans a high dimension space. For part, this work is motivated by multimedia data retrieval in databases.
Team considers the data processing and management task in distributed systems (clusters and peer-to-peer).
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COLOSS (COmposants et LOgiciels SûrS)
The research activities of the COLOSS Team range from Fundamental Research to Applications.
The main goal is the elaboration of concepts, methods and techniques supported by tools for software designers and developers.
Team explores formal approaches (based on mathematical foundations) to the assistance and the analysis in the development of software:
- Multi-formalism specification and analysis of software systems
- Specification, verification and validation of components and software architectures.
The goal is to ensure correctness of components used and their composition in complex software systems.
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MOVES (Modeling and Verification of Embedded Systems)
We are interested in the analysis of timed systems and the applications to embedded systems and bio-informatics.
Our main research themes are:
- verification of timed and hybrid systems
- timed extensions of Petri nets
- control of timed systems
- application of the previous models and technics to genetic regulatory networks.
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The research team “Psychology, Cognition, Technology” develops research projects on the human operator’s cognitive processes in human-machine systems for dynamic situation management (under partial control). Thus, the studies are performed on a multidisciplinary basis with engineering sciences (control theory and computer science), toward two prospects: human-machine cooperation and human cognition modelling.
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The research activities of the Robotics team can be classified according to the three following parts:
- Modelling, identification and control of manipulators: the objectives are the enhancement of the static and dynamic performances of robots.
- Mobile robots: first theme deals with modelling and control of wheeled robots, flying robots, walking robots and swimming robots.
-Teleoperation and environment modeling
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The constraint team is focusing on an approach that integrates, in a transparent way, the languages and the different techniques underlying constraint programming. The idea is mainly to develop generic techniques enabling both the integration and unification of the different aspects and new extensions of constraint programming.
The team aim to develop the practical application of constraint programming and to make it evolve to meet the needs of industry and/or academia. The three main topics we are already working on are geometric constraints, problems based on graphs and dynamic problems - mission planning, management of refineries.
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MODAL (Software Architecture Modeling Languages)
The MODAL group gathers research activities of two domains:
- Software architecture specification and design models.
- Structural and behavioral evolution models for software architecture.
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TALN (The Natural Language Processing Team)
Linguistic data is present in all media in the form of texts written or transcribed from sound tracks, subtitling, or annotations, etc. For access to document contents of all types it is essential to interface syntax and semantics and identify the relevant information using linguistic analysis. The Natural Language Processing Team is interested in grammatical inference, text mining and, in particular the acquisition of multilingual linguistic resources. It explores textual data to extract linguistic information concerned with all levels of language processing: morphological, lexical, syntactical, semantic and pragmatic, and analyses these levels it to give access to information conveyed.
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