Name : MichaŽl Aupetit
Michael Aupetit received his M.Sc. degree in computer science engineering from the Ecole pour les Etudes et la Recherche en Informatique et Electronique (EERIE, Nimes, France) in 1998. He obtained his Ph.D. with highest honor in Industrial Engineering from the Institut National Polytechnique de Grenoble (France) in 2001. He worked for 6 years at CEA DAM applying Machine Learning tools to analyze and monitor seismic events. Now he is with the Multi-sensor intelligence and machine learning laboratory (LIMA) at CEA LIST. His research activities cover Machine Learning, Data Mining and Visualization dealing with high-dimensional quantitative data.
MichaŽl Aupetit, Visualizing distortions and recovering topology in continuous projection techniques. Neurocomputing, 70(7-9), March 2007, 1304-1330, Elsevier.
Gaillard Pierre, MichaŽl Aupetit, Gťrard Govaert. Learning topology of a labeled data set with the supervised generative Gaussian graph Neurocomputing, 71(7-9)† March 2008, 1283-1299, Elsevier.†
Title of Project : Data mining and profile classification based on exploratory visualization and topology learning
In this research project, we study new visualization and statistical tools to discover hidden paths between individuals given their profile based on numerical attributes and eventually the communities they belong to. We intend to answer questions like: Is this profile atypical? Does it exist a continuum of profiles which connects one individual to another one? What are the underlying communities of individuals? Given identified communities, how likely individuals of one community are to contact individuals of other communities? And how likely they are to join another community?† Given identified leaders, how likely other individuals are to join such-and-such?