Abed is a postdoctoral research associate working on subgrid-scale parametrization of land-surface interactions for heterogeneous surfaces with specific focus on the Arctic pole. His research interests are interdisciplinary at the crossing between artificial intelligence, applied mathematics and environmental fluid mechanics. Prior to joining the TUNE lab, his primary work was centered over state estimation through downscaling and data assimilation, employing data-driven techniques such as deep learning and deep reinforcement learning. In addition, he conducted studies related to uncertainty quantification, reduced order models and sensitivity analysis in application to marine pollution and oceanic remote sensing.