Mr. Chao Liu is an active researcher in computer science with a strong focus on knowledge graphs, natural language processing, and big data analysis, particularly in the context of graph neural networks (GNNs). He has authored 33 scholarly documents that have attracted 492 citations across 488 citing publications, reflecting a high level of visibility and influence within the research community. With an h-index of 11, his work demonstrates consistent academic impact, especially in large-scale graph learning and data-driven intelligence. His recent contributions explore fundamental challenges in sampling-based large-scale GNNs, examining the relative roles of sampling strategies versus iterative computation for improving scalability and performance. Notably, his 2026 journal article in Neurocomputing, titled “Which plays a key role in sampling-based large-scale GNNs, sampling or iteration?”, provides important theoretical and empirical insights into efficient GNN design. Overall, his research advances scalable machine learning methods for complex, data-intensive systems.