Professor and deputy director, Department of Computer Sicence, École normale supérieure. Head of the Valda Inria team. Adjunct professor, Télécom Paris. Research fellow at the Centre on regulation in Europe.
Topics of interest
Data management, uncertainty, provenance, large-scale networks
Project in Prairie
Pierre Senellart’s research deals with management and mining of large-scale structured and semi-structured data in general, and largescale networks in particular, addressing issues such as management of the provenance, privacy, and uncertainty of data, and scalability through leveraging the structure of data. He is a co-coordinator of the PSL graduate program on data science and AI, in particular teaching within the PSL IASD Master.
Uncertain data are pervasive in artificial intelligence systems: input data are often imprecise, incomplete, or even contradictory, while automatic tools run on these data often produce imperfect annotations or predictions. A major challenge is to properly manage this uncertainty in data, keeping track of the confidence in individual data items throughout complex processes. For explicability and traceability purposes, it is also important to keep track of the provenance of data: where it comes from, how it was produced, etc. Uncertainty and provenance management are two of the main research issues in modern data management.