• Research Director in Computer Science: Data engineering, data analytics, and machine learning, IRD, France.

Team position: member, Synthesis Strand

Background: My research is focused on designing methods and software systems that assist users in complex and necessary tasks for data intelligence and machine learning. These tasks include data management, integration, fusion, cleaning, and preparation that scale to very large data sets. The final goal is to let the users focus exclusively on the logic of their application, without being concerned by the underlying models or the execution details. My applied work aims at providing end-to-end analytical pipelines (in Python) on the following key aspects of Data Science:

  • Detection and automatic correction of anomalies;
  • Data cleaning, integration, fusion, and preparation stack for data analysis and ML;
  • Detection of information falsification, fact-checking and truth discovery;
  • Applied machine learning with use cases in urban computing, healthcare, environment, and Earth Observation sciences.

Key disciplines and skillsets: Machine Learning, data management, data integration, statistics

Expectations: To contribute to the better understanding and management of protected areas leveraging Data Science; to prevent natural resource degradation with the hope that AI can help; to participate to united efforts in the PARSEC multidisciplinary project.

Contact: laure.berti (at)