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.

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Research at XGraph

graph dynamics

Spectral Theory on Varying Graphs

Explore the spectral theory on dynamic, directed, heterogeneous graph representations.

Multiple Network Interaction

Investigate the interaction of coupled flows across heterogeneous graphs.

Higher-order Analysis on Graphs

Develop higher-order analysis methods for graph flows.

Graph Bayesian Optimization

Investigate uncertainty quantification on graph flows.

LLM for Graphs

Explore the use of LLM for graph flows.

Transdisciplinary Graph Flows

How to integrate multidisciplinary advances in graph flows.

Genomics & Graphs

Look at the use of graph flows in genomics.

Brain Graphs

Investigate the use of graph flows in brain research.

Research Infrastructure

Develop infrastructure for graph flow research.


Sole-PI: develop undergraduate research experience on graph dynamics. Support native students to conduct research on graph dynamics.
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Global Development Grants
PI: Develop international relationship with New Zealand. Through this grant, we will develop a collaboration with the University of Auckland in New Zealand.
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Graph AI Working Group
PI: Develop a working group on Graph AI comprised of academic members from social science, biomedical, supply chain, and geoscience.
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Co-PI - Developing Detection and Modeling Tools for the Geospatial and Environmental Epidemiology of Animal Disease.
Sole PI - CRII: Interpretable Influence Propagating and Blocking on Graphs, Interpret the influence propagation and blocking on graphs.
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Co-PI - Advancing Agricultural Research through High Performance Computing
Zhiqian Chen 👨🏻‍💻

Zhiqian Chen

PI, Assistant Professor

Mississippi State University

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