Three priority research themes
Since its creation, the research centre has developed a policy of extremely close collaboration with the major institutions in the regions in which it is based, by setting up joint laboratories and teams.
Our scientific challenges
The Institute's strategic plan orients the Saclay centre's research towards three priority themes:
Software security and reliability
In fields such as transport, health, energy and telecommunications, software is becoming increasingly complex. Formal methods can be used to eliminate any error in order to certify trusted software.
In order to make the critical components of computer systems more dependable, it is necessary to develop advanced models for security and program analysis methods that are supported by tools that allow scaling-up. The work is based on advanced mathematical knowledge: elliptical curves for cryptography, type theory as a support for computer-assisted proofs, probabilistic models, etc. The aim is to offer methods and tools that raise users' confidence in computational technologies using a rigorous mathematical approach.
High Performance Computing and distributed knowledge on the Web
Migrating to a web of structured knowledge means it is necessary to provide services based on heterogeneous information and to extract knowledge from the text. The use of complex data for high-performance computing means it is necessary to develop computing models with suitable networks.
Miniaturisation and the multiplicity of computing and storage components are bringing about profound changes in data handling and computing models. Data may come from sensor networks or distributed resources on the Web. In order to find and organise these data, new exploration, restitution, interaction and visualisation methods must be designed, with a particular emphasis on learning techniques. Computing capacities are growing but are based on heterogeneous, dynamic and distributed components. Their use for high-performance computing requires the development of new computing models, particularly those based on computing grids, as well as new architectures and suitable compilation techniques. It raises new questions: efficiency, fault tolerance, new algorithms and programming models, new communication protocols.
Modelling, simulation and optimisation of dynamical complex systems
Amongst other things, this simulation makes it possible to build mathematical evolution models for plants and to understand how the human brain works.
Complex dynamic systems appear in many fields, both natural (physics, biology) and artificial (internet). They can be modelled using various approaches (partial differential equations, evolutionary systems, discrete or continuous, deterministic or stochastic models, numerical or algebraic resolution). The main fields of investigation concern image processing, particularly medical imaging, shape recognition, construction of evolution models for plants, organ ageing or understanding the functioning of the brain. The issues of optimisation and robust control of these systems, as well as their fault-tolerance, remain difficult.
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