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Research activities: Large scale modelling
The pervasive theme of data science and big data is faced by A&O/TAO in the context of autonomic computing and grid computing for e-Science. In the first case, the point is to model and ultimately manage a 100,000+ core system (the EGEE grid). In the second case, the point is to exploit data from scientific experiments to support the scientist search for hypotheses compatible with the available data and new experiments to discriminate among these hypotheses.

  Learning and Optimization

Joint Inria project teams

Research highlights

Contracts & grants

Software & patents


  YE Lina
  FERRE Arnaud

Ph.D. dissertations & Faculty habilitations

Research activities
° Algorithm control and hyper-parameter tuning
° Algorithms for networked systems
° Automated Proof, SMT and Applications
° Automated Reasoning
° Combinatorics
° Compilation and code optimization
° Data-Centric Languages and Systems
° Deductive Verification of Programs
° Distributed algorithms
° Engineering of interactive systems
° Formal Model-Based Testing
° Formalisation and Proof of Numerical Programs
° Formalisation of (Specification and Programming) Languages in Proof Assistants
° Generative design methods
° Graph Theory
° Green networks
° Heterogeneous Wireless Networks
° High-performance computing
° Human-Computer Interaction
° Integration of Data and Knowledge
° Interaction and visualization paradigms
° Massively distributed algorithms for complex data
° Mediated collaboration
° Multi-hop wireless networks
° Network coding