Zhiqian Chen 👨🏻‍💻

I am an Assistant Professor in the Computer Science and Engineering Department of Mississippi State University. Before joining MS State in 2020, I worked as a research assistant at Virginia Tech. I am now working on machine learning, with a particular emphasis on graph/network problems such as graph flow, see my research interest.

Collaboration at paper/proposal level is highly welcomed. Check my office hours for meeting. Students who want to work with me may check opennings. See my recent investigation at myrelated.work.
  • [Paper] 9/23: Theoretical Framework for Unifying GNN to appear in ACM Computing Survey, see preprint

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

  • [Fund] 8/23: USDA-ARS funded project focused on computational biology, where we will delve into the intricacies of connectivity within genome sequences. Special thanks to the support from CVM

  • [HIRING] 6/23: One undergraduate is needed for research on sleep pattern, ADHD, brain network and psychological signals

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

  • [Fund] 10/22: undergraduate research program funded by MS state ORED

  • [Fund] 4/22: Appreciate NSF’s support for my research on graph flow!

  • [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
  • [Paper] 10/21: Recent works have been selected by AAAI 22’, including graph wavelet, influence maximization, graph learning for hieroglyph, graph dynamics mapping

  • [Tutorial] 5/21: See our tutorial Spreading Model for Epidemics (GNN, RNN, SIR and PDE) in SDM 21’

  • [Paper] 12/20: One paper on citation forecast is accepted by AAAI 21’.

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

  • [Paper] 3/20 A survey for Graph Neural Networks (GNN) is online: preprint. See more GNN papers here

  • [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