During the last decade, the profusion of available data in a wide range of application domains rise up new challenges and opportunities in a plethora of disciplines ranging from science and engineering to biology and business. One major challenge is how to take advantage of this unprecedented scale of data – typically of heterogeneous nature (texts, images, graphs, sequences, etc.) – in order to acquire further insights and knowledge for improving the quality of the offered services. This is where Data Science comes in.

Data Science rises as a challenging discipline capitalizing in different sciences and methods including informatics and applied mathematics. It is by nature a multi-disciplinary field, which beside the above mentioned disciplines, requires a deep understanding of the field to which it is applied.
Professional Training
  • M2-master in Data Science
  • DIX/CMAP PA in Bigdata
Relevant Events
  • Research Initiative "Numerical methods for control - Stochastic", Fime laboratory
  • INRIA Select, INRIA Parietal
  • Partnership with supplier of high frequency data QuantHouse
  • Thales

Position paper: "Search in BigData2 – When Big Text meets Big Graph", presented on the World Summit on Big Data and Organization Design, IBM, Organizational Design Community, & Interdisciplinary Center for Organizational Architecture/ Aarhus University, May 16-17, 2013 in Paris.

Search in BigData2
When Big Text meets Big Graph

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