This work focuses on the analysis of social networks or interaction networks in order to detect communities or behaviours. Temporal evolution of interactions and communities is a major concern.
The approaches used are:
- detection of temporal communities in graphs that may have attributes on nodes and/or edges
- graphlet identification (small induced subgraphs)
- machine learning tools for classification and clustering
- 2D visualization tools for community evolution
This work aims to use techniques from the analysis of social networks and machine learning to produce Learning Analytics (LA) that will support learners and teachers in changing their practices.
We are particularly interested in how the analysis of social interactions allows us to obtain insights into the dynamics of learning strategies.
According to the World Health Organization, starting from 2010, cancer will become the leading cause of death worldwide. Prevention of major cancer localizations through a quantified assessment of risk factors is a major concern in order to decrease their impact in our society. In this project our objective was to find and to evaluate modeling methods easily readable by a physician.
This work aims to develop new methods of data exploration and analysis using immersion techniques in 3D environments.
We are particularly interested here in the development of graph visualization techniques to allow:
- an intuitive visualization of the centrality of nodes
- the ability to navigate between several levels of detail
The purpose of this work on pedagogy in higher education is to take a step back on the various pedagogical innovations implemented in my teaching activities at IMT Atlantique.
Several topics are covered:
- student motivation and autonomy
- skill assessment
- peer review
- the management of heterogeneous populations