Graphs are a unifying abstraction that leverages connectedness to represent, explore, predict, and explain real-life and digital-world phenomena. Examples include social network graphs representing connections between users or graphs representing transactions between participants in cryptoasset ecosystems like Bitcoin. In recent years, we are witnessing an unprecedented growth of graph datasets across domains. Here at AIT, we investigate and apply novel algorithmic methods for processing and learning from large, connected datasets to support evidence-based decision-making.