I am a member of the research team STeamer at the Laboratoire d’Informatique de Grenoble, team which I directed from 2010 to 2015, and which conducts research in Computer Science, in interaction with Geographic Information Sciences (field identified in France by the term “geomatics”).

Geographic Information Sciences, a scientific field at the intersection of several disciplines, aim at proposing methods and tools to model, integrate, analyze, simulate and visualize geographic data.

STeamer team places at the center of its research the representation and processing (reasoning, inference, visualization, analysis, …) of information with spatial and temporal references. The research within the team is articulated along 3 axes:

  1. SpatioTemporal Semantic Web;
  2. Crowdsourcing and Social Choice;
  3. Visualization and Analysis of SpatioTemporal Informationi.

My different researches are in line with these 3 axes since 2007 (date of creation of the STeamer team).

Currently, and since my CRCT, my researches address essentially the problems related to Semantic Trajectories, mainly those of Territories (political, administrative, socio-economic trajectories, etc.) and those of  Individuals (family, residential, professional, health trajectories, etc.).

To study these composite and complex spatio-temporal objects, I rely on the representation and analysis tools of the Semantic Web and Machine Learning.

In terms of modeling, existing ontology languages and standard vocabularies make it possible to account for the multidimensional aspect (temporal, spatial and multi-thematic) of semantic trajectories.

In terms of analysis, these semantic trajectories are understood as temporal sequences of multidimensional and heterogeneous data. The analysis axes mainly concern the classification and the search for recurrent patterns. The underlying challenges are the design of adapted similarity measures and the reduction of the high dimensionality of these data sequences.