Hejie Cui

Hejie Cui

Doctoral Student in CS

Emory University

Biography

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 multimodal data mining and AI for health informatics. Check my CV for more details.

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.

News

  • [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).

Interests

  • Multimodal Learning with Graphs
  • AI for Health and Neuroscience
  • Language and Vision Knowledge Mining

Education

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

    Emory University

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

    Tongji University

Experience

 
 
 
 
 

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

Amazon

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

Research Mentorship Program

Google

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

SAP

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

Selected Accomplishments

  • Rising Stars in EECS (Georgia Institute of Technology), 2023
  • KDD Student Travel Grant Award, 2023
  • 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

Talks

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.

Services

  • Program Committee Member / Reviewer:
    • Conference: 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)