Dr. Yuri Gelsleichter is a soil and geomatics researcher focused on AI-driven predictive models. His research combines proximal soil sensing, using Vis-NIR and mid-infrared spectroscopy, with multi- and hyperspectral imagery and machine learning to map, and predict soil attributes. Experienced in HPC environments, he builds reproducible workflows using open-source tools such as R, Python and GDAL. He has contributed to international initiatives, including the EU Horizon 2020 Soils4Africa project (soil information system), and the OSIRIS project on science reproducibility. He collaborates with research groups across the Americas, Europe, Africa and Oceania. His broader expertise encompasses pedometrics, soil genesis and classification, data visualization, and spatial analysis.