I have completed my BSc and MSc degrees in the field of Environmental Sciences and Technology, with a particular emphasis on employing remote sensing and Earth observation data to address ecological and environmental changes. During my PhD in Biodiversity, Genetics and Evolution, I studied the effects of wildfires on several key aspects of ecosystem functioning, as well as their responses to such disturbances — more specifically post-fire severity, recovery, and resilience -, using a satellite-based approach. With almost 15 years of experience, I have employed a diverse set of methods and techniques for data analysis - including statistical analysis, modelling, and machine learning -, with both geospatial and non-geospatial data. I use several different software packages and environments (e.g. QGIS, ArcGIS), including mainly open-source code-based workflows and pipelines (e.g. R, Python). Among others, my main scientific contributions and interests include: (i) gathering, (pre-)processing, and extracting information from remotely sensed data (e.g. satellite image time-series); (ii) characterizing ecosystem functioning at regional, national, and continental scales; (iii) analyzing patterns of biodiversity (in a broader sense) and environmental changes; and (iv) assessing and modelling the occurrence, severity, recovery, and resilience of ecological disturbances (e.g. wildfires).