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.


  • 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.


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


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

    Emory University

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

    Tongji University



Applied Scientist Intern


May 2022 – Aug 2022 Seattle, Washington, United States
  • Worked in the Product Knowledge Graph Team
  • Project: Attributed value extraction for Amazon product knowledge graph construction

Research Mentorship Program


Feb 2022 – May 2022 Remote
  • Discussed potential student researcher project on GNN for retrieval/recommendation and wrote up a short proposal.
  • Mentor: Masrour Zoghi

Research Intern


Dec 2018 – Jul 2019 Beijing, China
  • Worked in the Intelligent Health Team
  • Project: Developed a pulmonary vessel segmentation algorithm, an orthogonal fused U-Net++, for chest CT images
  • Achievement: Got a patent filed and one paper accepted to MICCAI (tier-1 conference in medical imaging)

Mitacs Global Research Intern

Queens University

Jul 2018 – Oct 2018 Kingston, Ontario, Canada
  • Worked in Prof. Gabor Fichtinger‘s Perk Lab
  • Project: Improve Center Line Tutor by Deep Learning, directed by Prof. Gabor Fichtinger
  • Achievement: Designed a framework for providing real-time feedback in central venous catheterization training and built an extension for web-cam video image classification using Tensorflow in 3D Slicer

Microsoft University Summer Camp

Microsoft Research Asia

Aug 2017 – Aug 2017 Beijing, China
  • Project: Prototype Workflow for HoloLens Mix-reality Applications
  • Achievement: Best work award for university summer camp Hackathon

SAP Student Training and Rotation Program


Jun 2017 – Aug 2017 Shanghai, China
  • Project: ABAP development

Selected Accomplishments

  • NeurIPS AI4Science Travel Award, 2022
  • NSF Student Travel Grant Award for CIKM, 2022
  • Laney Graduate Student Council Travel/Research Grant, Emory University, 2022
  • MICCAI Student Travel Grant Award, 2022
  • Fellowship of 2021 CRA-WP Grad Cohort for Women, 2021
  • Emory University Graduate Fellowship, 2019
  • Valedictorian of the School of Software Engineering Class 2019, Tongji University, 2019
  • Outstanding Graduate of Shanghai, 2019
  • Globalink Research Award for International Undergraduate Research in Canada, 2018
  • Tongji University Programming Competition, Silver Prize, 2017
  • National Scholarship of China, 2016, 2017, 2018


BrainGB: A Benchmark for Brain Network Analysis with Graph Neural Networks

Give a talk about our benchmark work on GNNs for brain networks. Slides are available here.

Effective and Interpretable Graph Neural Networks for Graphs Constructed from Multimodality Data

Give a talk about my work on Effective and Interpretable Graph Neural Networks for Graphs Constructed from Multimodality Data. Slides are available here.


  • Program Committee Member / Reviewer:
    • Conference: SIGKDD'22,23; ICDM'22; WWW'22; AAAI'21,22; MICCAI'20,22,23; SDM'22; LOG'22
    • Journal: TKDE, IEEE BigData
    • Workshop: Temporal Graph Learning NeurIPS'22; Graph-Based Natural Language Processing COLING'22; Interpretable Machine Learning in Healthcare ICML'21,22; Computer Vision for Automated Medical Diagnosis ICCV'21; Medical Imaging meets NeurIPS'21
  • Organizer:
    • Neural Networks for Brain Connectome Analysis: Theories, Methods, and Applications Workshop IEEE BigData'22
    • Federated Learning with Graph Data Workshop CIKM'22
  • Volunteer:
    • International Conference on Machine Learning ICML'20,21
  • Teaching:
    • CS 253 Data Structures and Algorithms, TA (Spring 2021)
    • CS 584 Natural Language Processing for Biomedical Applications, Head TA (Fall 2020)
    • CS 584 Deep Learning, Head TA (Spring 2020)
  • Leadership: Chairperson, Microsoft Student Club, Tongji University (2017-2018)