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 also go by the name Callie. 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 interpretable machine learning, graph data mining, multi-modal learning, knowledge graphs, as well their applications in neuroscience and healthcare.

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

  • [2022.8.1] Short paper on artificial node features for applying GNNs on non-attributed graphs got accepted to CIKM 2022.
  • [2022.7.27] Invited as a PC member for AAAI 2023 regular track and the special track on AI for social impact.
  • [2022.7.21] Invited as a reviewer for TextGraphs workshop on COLING 2022.
  • [2022.6.23] We will be organizing the 1st International Workshop on Federated Learning with Graph Data FedGraph2022, at CIKM 2022, in Atlanta, Georgia this October. Various types of submissions are welcomed!
  • [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 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 (Seattle). Drop me a message if you wish to grab a coffee together!
  • [2022.4.15] We will be organizing the 1st International Workshop on Neural Network Models for Brain Connectome Analysis BrainNN2022, at IEEE BigData 2022, in Osaka, Japan this December. Various types of submissions are welcomed!

Interests

  • Graph Machine Learning
  • GNNs for Multimodality Data
  • Knowledge Graphs
  • Commonsense Reasoning

Education

  • PhD in Computer Science, 2019-now

    Emory University

  • BEng in Software Engineering, 2015-2019

    Tongji University

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