The challenges related to the use of massive amounts of data (e.g omics data, imaging-genetic data, etc) include identifying the relevant variables, reducing dimensionality, summarizing information in a comprehensible way and displaying it for interpretation purposes. Often, these data are intrinsically structured in blocks of variables, in groups of individuals or in tensor. Classical statistical tools cannot be applied without altering their structure leading to the risk of information loss. The need to analyze the data by taking into account their natural structure appears to be essential but requires the development of new statistical techniques that constitutes the core of my research for many years. In particular, I am interested in multiblock, multigroup and multiway structures.