XGraph emphasizes the movement of everything flowing over graphs, representing a dynamic field where data, resources, entities, or influences flow through graph structures.
Flow analytics in social networks pinpoints key influencers, tracks information flow, and locates communication blocks. In the internet/transport systems, it ensures efficiency, durability, and growth. Within biological networks, it aids in understanding protein interactions and disease transmission. Thus, flow analytics is crucial for revealing the behavior of interconnected systems, driving the creation of sophisticated methods for analyzing graph flows in the real world.
graph dynamics
Explore the spectral theory on dynamic, directed, heterogeneous graph representations.
Investigate the interaction of coupled flows across heterogeneous graphs.
Develop higher-order analysis methods for graph flows.
Investigate uncertainty quantification on graph flows.
Explore the use of LLM for graph flows.
How to integrate multidisciplinary advances in graph flows.
Look at the use of graph flows in genomics.
Investigate the use of graph flows in brain research.
Develop infrastructure for graph flow research.