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