Karen Tatiana Bastidas Méndez is a Cadastral and Geodesy Engineer specialized in Artificial Intelligence and currently pursuing a Master’s degree in Remote Sensing at the Universitat de València, Spain. She has more than five years of professional experience in satellite image processing, land-cover and land-use classification, spatiotemporal change detection, and computer vision for Earth observation. Her work integrates machine learning and deep learning approaches, including semantic segmentation, object detection, neural network–based plant detection, and environmental monitoring. She has contributed to large-scale geospatial initiatives in Colombia, including the first national land-cover raster map harmonized with the CORINE Land Cover legend, developed by Fundación Natura, IDEAM, and Ecopetrol, and has broader experience with MapBiomas-based mapping workflows for land-cover and land-use monitoring. Her technical expertise includes Python, R, Google Earth Engine, Azure Databricks, and Google Vertex AI, with applied experience in multitemporal analysis, reproducible geospatial workflows, and deep learning models for geospatial applications.