Progress in technology (connecting objects, monitoring devices, sensors, remote sensing, neuroimaging, etc.) makes it possible to collect data in some sort of continuum. The continuum may be related to time or space, but could also originate from multiple sources. In those problems, a statistical unit may be a curve, a surface or any more complex mathematical object having some continuum feature.

Such data are called functional data, where the word "functional" is the natural mathematical concept for handling continuum. The challenge is simple: extract relevant information from datasets containing collections of curves, or surfaces or any other complex objects, often combined with standard multivariate variables. Techniques dealing with such functional data are all gathered under the Functional Data Analysis (FDA) terminology .

The success of this exciting modern area of Statistics is mainly due to its ability to solve major hi-tech engineering challenges coming from important domains of applications (biology, biomechanics, chemometric, econometrics, environmental management, geophysics, image processing, medicine, remote sensing, etc.) while raising new theoretical issues.

Time has come to consolidate the recent progress in this area and provide a platform for researchers to exchange ideas, start collaboration on scientific projects and build a robust inferential framework for functional data analysis that considers the increasing complexities of the data. This workshop is intended to bring together, in West Africa (Senegal), the leaders in this field, representatives of application areas, and promising young researchers to pave the path for future development in the field.