Hejie Cui

Hejie Cui

Doctoral Student in CS

Emory University

Hi there! This is Hejie Cui (pronounced as “Her-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 data mining, knowledge acquisition and infusion with deep language/vision models, as well as effective and interpretable graph learning methods for neuroscience and healthcare. 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.

News

  • I will join Microsoft Research - Redmond as a Research Intern in Summer 2023.
  • [2023.1.22] Two papers on deep structure learning and hierarchical clustering got accepted to ISBI'23. Congrats to Yue and Wei!
  • [2022.12.22] Invited as a reviewer for KDD'23 Research Track.
  • [2022.11.19] One paper on few-shot learning is accepted to AAAI'23 as Oral . Congrats to Ran!
  • [2022.11.7] Glad to receive NeurIPS AI4Science Travel Award.
  • [2022.10.21] Benchmark work on Graph Neural Networks for Brain Networks has now been officially accepted to IEEE TMI (IF: 11.037) . Great thanks to my collaborators!
  • [2022.10.19] One paper on multi-view network analysis got accepted to BIBM'22.
  • [2022.9.14] One paper on graph transformer got accepted to NeurIPS'22 as Spotlight . See you in New Orleans!
  • [2022.8.1] One paper on GNN node features for non-attributed graphs got accepted to CIKM'22.
  • [2022.6.3] One paper on interpretable GNNs got accepted to MICCAI 2022 as Oral .
  • [2022.6.2] One paper on multi-task meta-learning got accepted to KDD'22.
  • [2022.5.30] One Paper on network generation guided by task-aware GNNs accepted at MIDL'22 as Oral .
  • [2022.5.16] Started my research internship at the Amazon Product Knowledge Graph Team.

Interests

  • Graph Data Mining
  • Knowledge Graphs
  • Knowledge Acquisition and Infusion with Deep Language/Vision Models
  • AI for Health

Education

  • Ph.D. in Computer Science, 2019-now

    Emory University

  • B.Eng. in Software Engineering, 2015-2019

    Tongji University