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 final-year PhD student in Computer Science at Emory University, advised by Prof. Carl Yang. My research focuses on the integration of multimodal data mining and knowledge-empowered interpretable model for health informatics. Check my CV for more details. Lately, I am interested in the evaluation of large multimodal models for health and exploring data-centric AI approaches for foundational health models. If our research interests align, I would be delighted to discuss potential collaborations. Please don’t hesitate to reach out via message or email.

Previously, I got my bachelor’s degree (Valedictorian, GPA Ranking: 1/164) 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.


  • [2023.09] One paper on visual knowledge extraction with multimodality model prompting is accepted to NeurIPS'23. Thanks to my collaborators.
  • [2023.09] Two papers on brain network analysis are accepted to PSB'24. Congrats to Alexis (High-Schooler)!
  • [2023.08] Selected to participate in the 2023 EECS Rising Stars Workshop!
  • [2023.07] One collaborative paper on dynamic graph is accepted to IEEE-BHI'23.
  • [2023.06] Our survey paper on healthcare knowledge graph resources, applications, and promises is now accessible online. To be appeared at ICML-IMLH'23.
  • [2023.05] One collaborative paper on biological data augmentation is accepted to KDD'23.
  • [2023.05] One paper on multimodality information extraction is accepted to the Findings of ACL'23 and selected as Oral at the KDD Workshop on Knowledge Augmented Methods for NLP (KnowledgeNLP-KDD23).
  • [2023.04] Our paper on GNN pre-training on brain networks is accepted to CHIL'23 (Oral). Glad to receive a Travel Grant! See you in Boston in June.
  • [2023.02] I will join the Augmented Learning and Reasoning Group at Microsoft Research Redmond as a Research Intern in Summer 2023.
  • [2023.01] Two collaborative papers on structure learning got accepted to ISBI'23.
  • [2022.11] One collaborative paper on few-shot learning is accepted to AAAI'23 (Oral).
  • [2022.11] Glad to receive NeurIPS AI4Science Travel Award!
  • [2022.10] One Benchmark paper on Graph Neural Networks for Brain Networks has now been officially accepted to IEEE TMI (IF: 11.037).
  • [2022.09] One collaborative paper on transformer is accepted to NeurIPS'22 (Spotlight).
  • [2022.08] One paper on GNN node features is accepted to CIKM'22.
  • [2022.06] One paper on interpretable GNNs is accepted to MICCAI'22 (Oral).
  • [2022.06] One collaborative paper on meta-learning is accepted to KDD'22 (Health Day).


  • AI for Health
  • Multimodality Machine Learning
  • Brain Networks Analysis
  • Data Science and Mining


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

    Emory University

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

    Tongji University



Research Intern

Microsoft Research

May 2023 – Aug 2023 Redmond, Washington, United States
Worked in the Augmented Learning and Reasoning Group, Office of Applied AI Research, and MSAI.

Applied Scientist Intern


May 2022 – Aug 2022 Seattle, Washington, United States
Worked on multimodality knowledge extraction in the Product Knowledge Graph Team.

Research Mentorship Program


Feb 2022 – May 2022 Remote
Worked on GNN for recommendation with Masrour Zoghi.

Mitacs Global Research Intern

Queens University

Jul 2018 – Oct 2018 Kingston, Ontario, Canada
Visited Perk Lab and worked on video detection for surgery training with Prof. Gabor Fichtinger

Microsoft University Summer Camp

Microsoft Research Asia

Aug 2017 – Aug 2017 Beijing, China
Project ``Prototype Workflow for HoloLens Mix-reality Applications’’ got the best work award for Microsoft summer camp Hackathon

SAP Student Training and Rotation Program


Jun 2017 – Aug 2017 Shanghai, China
Worked on ABAP database

Selected Accomplishments

  • Rising Stars in EECS, 2023
  • KDD Student Travel Grant Award, 2023
  • NeurIPS AI4Science Travel Award, 2022
  • NSF Student Travel Grant Award for CIKM, 2022
  • Laney Graduate Student Council Research Grant, Emory University, 2022
  • MICCAI Student Travel Grant Award, 2022
  • Award for CRA-WP Grad Cohort for Women, 2021
  • Mitacs Globalink Research Award, 2018
  • Valedictorian of the School of Software Engineering Class 2019, Tongji University, 2019
  • Outstanding Graduate Award, the City of Shanghai, 2019
  • Outstanding Graduate Award, Tongji University, 2019
  • Tongji University Programming Competition, Silver Prize, 2017
  • National Scholarship, 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: ICLR'24; NeurIPS'23; ML4H'23; CHIL'23; SIGKDD'23,22; ICDM'22; WWW'22; AAAI'23,22,21; SDM'22; LOG'22; MICCAI'23,22,20;
    • Journal: TKDE, TMI, IEEE BigData
    • Workshop: Temporal Graph Learning NeurIPS'22; Graph-Based Natural Language Processing COLING'22; Interpretable Machine Learning in Healthcare ICML'22,21; 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:
    • Conference: CHIL'23; CIKM'22; ICML'21,20
  • 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)