Hejie Cui

Hejie Cui

Doctoral Student in CS

Emory University

Hi there! This is Hejie Cui (pronounced as “He-jay Tsuee”, 崔鹤洁 in Chinese). I am currently a PhD student in Computer Science at Emory University, under the supervision of Prof. Carl Yang in Emory Graph Mining (EGM) Lab. My research interests lie in graph machine learning, data mining, knowledge graphs, multi-modal learning, as well their applications in neuroscience and healthcare data. Check my CV for more details.

Previously, I got my bachelor’s degree in Software Engineering at Tongji University. During my undergraduate, I worked on computer vision for medical imaging with Prof. Lin Zhang. In addition, I worked with Prof. Tianwei Yu on machine learning for bioinformatics. I also spent a wonderful summer at Prof. Gabor Fichtinger‘s Perk Lab at the School of Computing, Queen’s University in Kingston, Canada through the Mitacs program.


  • [2022.11.19] One paper on few-shot learning got accepted by AAAI 2023. Congrats to Ran!
  • [2022.11.7] Glad to receive NeurIPS AI4Science Workshop 2022 Travel Award!
  • [2022.10.21] Our benchmark work “BrainGB: A Benchmark for Brain Network Analysis with Graph Neural Networks” has now been officially accepted to IEEE TMI (IF: 11.037). Great thanks to my collaborators!
  • [2022.10.19] Our work on multi-view brain network analysis with cross-view missing network generation got accepted to BIBM 2022.
  • [2022.9.14] Our work on brain network transformer got accepted to NeurIPS 2022. The previous version was selected as Oral for ICML-IMLH 2022. See you in New Orleans!
  • [2022.8.1] Short paper on artificial node features for applying GNNs on non-attributed graphs got accepted to CIKM 2022.
  • [2022.6.3] Paper on brain disease analysis with interpretable GNNs got accepted to MICCAI 2022 (among the top 13% provisionally accepted ones in 1,825 submissions).
  • [2022.6.2] Our work on cross-data brain networks got accepted to KDD 2022 Health Day.
  • [2022.5.30] Our work on functional brain network generation guided by task-aware GNNs has been selected for an oral presentation at MIDL 2022.
  • [2022.5.16] Started my research intern at the Amazon Product Knowledge Graph Team.


  • Graph Machine Learning
  • Knowledge Graphs
  • AI for Health
  • Multimodal Learning


  • PhD in Computer Science, 2019-now

    Emory University

  • BEng in Software Engineering, 2015-2019

    Tongji University