Dr.-Ing. Omid Abdi is a Researcher at the Department of Forest Sciences, University of Helsinki, Finland. With a strong educational background in geoinformatics and computer science, his research focuses on the intersection of GeoAI, remote sensing, and environmental modeling. Dr. Abdi has extensive work experience in developing robust machine learning and computer vision frameworks to address complex challenges in precision forestry, climate change, and natural hazard assessment (including soil disturbances, droughts, floods, and wildfires). His notable academic works include pioneering the use of Graph Neural Networks (GNNs) for mapping soil particle-size distributions, and developing hybrid Vision Transformer architectures for automated rutting depth prediction on logging trails. Currently, he is actively advancing dynamic digital soil mapping and AI-driven tree-ring segmentation in projects such as OptiForValue and GeoAISoil.