New technologies allow us to handle increasingly large datasets, while monitoring devices become ever more sophisticated. This high-tech revolution affords progressively more accurate observations, by producing statistical units sampled over a finer and finer gird. As the measurement points become closer, the data can be considered as observations varying over a continuum. Such continuous (or functional) data can be found in a wide variety of areas, including biomechanics, econometrics, geophysics, chemometrics, and medicine.

Frederic Ferraty is a researcher in Statistics at Toulouse University (France). He has been working on all facets of Statistics, ranging from fundamental theory basis, methodology developments to practical implementation. In addition, most of major topics of Statistics as Classification, Exploratory Methods, Regression, Time Series have been investigated. In the last decade, he mainly oriented his research towards high dimensional statistical problems involving systematically functional data. His numerous statistical contributions have been published in prestigious international statistical journals. He is also a prominent and very active member of the international statistical community through co-organizations of several international scientific events and numerous editorial works for publishers and statistical journals of high scientific level.

Yves Romain is an academic researcher at Institute of Mathematics of Toulouse (France). He is Doctor in Applied Mathematics and HDR in Statistics. His main research domains are multivariate analyses in large dimension and related fields such as operator-based statistics and backgrounds for statistics in infinite-dimensional spaces.