Ehsan Mobaraki

Ehsan Mobaraki is a Research Fellow at the Department of Computer Science within Aalborg University's Technical Faculty of IT and Design. His work focuses on Graph Neural Networks (GNNs), Explainable AI (XAI), and Data Analytics, with particular emphasis on uncertainty quantification and interpretability in machine learning systems.

Research Trends: Recent publications highlight his contributions to reducing uncertainty in GNNs, developing interpretability frameworks for deep learning, and advancing data management techniques. His work spans theoretical and applied aspects of Machine Learning and Neural Networks, with applications in network analysis and subgraph modeling.

Collaborations: Active collaborations with researchers like Arif Khan, Francois Bonchi, and Ylli Velaj demonstrate his engagement with the broader data science community. His research has been presented at prominent venues such as DSAA and GRADES-NDA.

Labs & Teams: Affiliated with the Data Engineering, Science and Systems group at Aalborg University, Mobaraki contributes to cutting-edge research in AI and data science, focusing on enhancing transparency and robustness in learning systems.