The main scientific area of activity is on Process Systems Engineering (PSE), even though other fields such as Process Analytics and Industrial Statistics can also be seen as targeted research areas. After an initial interest in First Principle model-based fault detection and diagnostic systems, the contact with processes lacking accurate mechanistic models shifted the research interests towards data-centric methodologies for process analysis, modelling, monitoring, control and improvement, as well as to other relevant issues regarding the generation of data with high quality (DoE, R&R studies, measurement uncertainty). The complexity of processes and data collected from them, motivated a concentration of efforts on high-dimensional multiscale data-driven approaches, that present the ability of adequately describing different phenomena going on at separate scales of time and length, through mathematical and statistical frameworks that incorporate the scale in the core of their algorithms, and where wavelet theory and multivariate statistics play key roles, when synergistically combined. A wide variety of methodologies have been proposed in this scope, for fault detection & diagnosis, soft sensors for critical properties, process analysis, system identification and optimization, sensor fusion, hybrid modelling, among others. I am also been actively involved in developments in the fields of Multivariate Image Analysis (MIA), analysis of gene expression data, biosystems, pulp & paper, process improvement through the six-sigma and lean manufacturing initiatives. (For more information on research activities, please visit my reserach website: http://www.eq.uc.pt/~marco/research/pclab/)