陈枳扦

陈枳扦 Chen, Zhiqian

Assistant Professor

Mississippi State University

I am an assistant professor in the Computer Science and Engineering Department of Mississippi State University. I am now working on machine learning, with a particular emphasis on dynamics behaviors over graphs/networks, see my research interest. For students who are interested in my research, please check ways to work with me.

Call for Proposal: Data Challenge at IEEE BigData 2024, and I am serving as a co-chair of the 2024 IEEE Big Data Cup Challenge.
  • [Tutorial] 2/24: our tutorial on Spectral and Spatial Graph Neural Network has been accepted at CVPR 24’. Look forward to our gathering in Seattle this summer! See our tutorial website at CVPR 24’ Tutorial.

  • [Fund] 1/24: Received NSF REU supp to fund undergraduate student research.

  • [Paper] 12/23: 2 papers are accepted by AAAI 24’ proposing Graph Bayesian Optimization to conduct information propagation efficiently.

  • [Paper] 12/23: Our theoretical framework for unifying GNN accepted by ACM Computing Survey, see paper, related work and slides.

  • [Tool] 12/23: Our custom GPT Research Reviewer (used in 1k+ chats) is listed as 1st returned result of Research Review at gptshunter and gpts.works. Check out our FlowGPT (117 chats), which demonstrates the energy evolution of disease spreading.

  • [Fund] 12/23: Received a Global Development Seed Grant Award from the International Institute to develop a collaboration with the University of Auckland in New Zealand.

  • [Fund] 12/23: Launch a working group on Graph AI comprised of academic members from social science, biomedical, supply chain, and geoscience. Thanks to Bagley College of Engineering for financial support.

  • [Tool] 8/23: XFlow is released, which targets to model generalized graph flows

  • [Fund] 8/23: USDA-ARS funded project on genomics. Special thanks to the support from CVM@MSState

  • [Paper] 12/22: One paper is accepted by SIAM Data Mining (SDM) 23’: how seeds interact in higher-order perspective

  • [Textbook] 7/22: Our textbook published by Springer Nature provides numerous code examples, Springer Nature, Amazon

  • [Fund] 4/22: Received NSF’s fund: CRII: Interpretable Influence Propagating and Blocking on Graphs

  • [Paper] 12/21: One paper is accepted by SIAM Data Mining (SDM) 22’

    • Graph Wavelet for Impact Forecast of Traffic Accidents, with SIAM Early Career Travel Award
  • [Tutorial] 5/21: See our tutorial Spreading Model for Epidemics (GNN, RNN, SIR and PDE) in SDM 21’

  • [Paper & Award] 9/20: Papers on Kalman filtering and school redistricting are accepted by ACM SIGSPATIAL 20’ with (Best Paper Award)

  • [Paper] 12/19: Unsupervised learning for material discovery is published in Nature Communications.

    • Selected as 22nd of Top 50 Chemistry and Materials Sciences Articles Top 50 Collection

Research Topics

on 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.

Grants, Awards & Honors

Sole-PI: Develop undergraduate research experience on graph dynamics.
See certificate
MSstate
Global Development Grants
PI: Develop international relationship with University of Auckland in New Zealand.
See certificate
MSstate
Graph AI Working Group
PI: Promote research from social science, biomedical, supply chain, and geoscience.
See certificate
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

Selected

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Higher-order Relation in Seeds
How remote seeds can implicitly ``interact’’ with each other in the influence maximization problem?
Higher-order Relation in Seeds
An Unified Framework for Graphs
Is there an unfying framework for all types of graphs, including spectral and spatial, also, directed, higher-order, and dynamic graphs?
An Unified Framework for Graphs
Graph Bayesian Optimization
How to conduct Bayesian optimization over graph problems so as to reduce data use?
Graph Bayesian Optimization
Machine Learning for Computer Scientists and Data Analysts: From an Applied Perspective
A textbook for practitioners and students in computer science and data analysis
Machine Learning for Computer Scientists and Data Analysts: From an Applied Perspective
Graph Learning with Kalman Filtering
Use Kalman filtering to handle uncertainty.
Graph Learning with Kalman Filtering
Graph Learning on Circuits
Ues graph neural network to model circuit, and predict its encryption attribute.
Graph Learning on Circuits
Graph Learning on Street Views
Use streetview to predict the crime statistics.
Graph Learning on Street Views

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