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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Granted Projects

NSF
NSF ITEST
Co-PI - SmartCT: Develop AI education program for K-12 students in Mississippi.
NSF
NSF CIRC
PI - Develop Grand Theory for Graph Dynamics.
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NSF
NSF REU - Supplement
Sole-PI: Develop undergraduate research experience on graph dynamics.
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MSstate
Global Development Grants
PI: Develop international relationship with University of Auckland in New Zealand.
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MSstate
Graph AI Working Group
PI: Promote research from social science, biomedical, supply chain, and geoscience.
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USDA
USDA-ARS
Co-PI - Developing Detection and Modeling Tools for the Geospatial and Environmental Epidemiology of Animal Disease.
NSF
NSF IIS
Sole PI - CRII: Interpretable Influence Propagating and Blocking on Graphs.
See certificate
USDA
USDA-ARS
Co-PI - Advancing Agricultural Research through High Performance Computing
Zhiqian Chen 👨🏻‍💻

Zhiqian Chen

PI, Assistant Professor

Mississippi State University

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