I am post-doc researcher in the Department of Electronic Engineering at the Rovira i Virgili University. I started my research carrier right after receiving an FPI scholarship from MINECO to work on my PhD Thesis within the same department. My work is focused on the development of technologies to apply mass spectrometry imaging (MSI) at metabolomics studies. In this regard, I have contributed to the development of a novel sputtering-base technique that allows a very controlled and homogeneous deposition of gold and silver nano-layersover a thin tissue section. This enables the detection of low-weight compounds in MSI with very high lateral resolution and non-interferingMS signals. However, my major work have been carried out in the field of creating software tools for MSI due to my background in software development, signal processing and data analysis. I wrote the code of two well-known software tools in the MSI community: rMSI and rMSIproc. Both are R packages which in combination are targeted to MSI data handling, exploration, visualization and pre-processing. The rMSproc package includes a novel label-free alignment algorithm that has demonstrated to be very reliable to minimize the effect of mass misalignment in MSI datasets. The suitability of my spectral alignment and mass re-calibration algorithm has been widely validated by successfully merging multiple datasets. I have stayed in Leiden University Medical Center (The Netherlands) for a period of 3 month by the end of my PhD. There, I have adapted all the developed technologies and software tools to FTICR high mass resolution spectrometers. Currently, I am contributing to the development of silicon-based surfaces for MSI and to the development of automated MS peakannotation algorithms to allow a fast and robust data interpretation of MSI. In addition, I am researching in the application of multivariate statistics tools to MSI data analysis. Finally, I continue to lead the rMSI and rMSIproc packages development in order to incorporate all the newly developed tools in future releases of both R packages.