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.
[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’
[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.
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.