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. I have also been working closely with Prof. Joyce C Ho on healthcare applications. In the past summers, I interned at Microsoft Research and Amazon Science.

Research Interests: My research lies at the intersection of machine learning, data mining, and health informatics. I aim to leverage advanced AI techniques to create innovative solutions that can support data-driven decision-making in healthcare.

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

• [2024.04] Happy to be selected for a poster presentation at the CHIL Doctoral Symposium!
• [2024.03] Our work on multi-agent LLM reasoning for few-shot disease prediction using electronic health records is available online.
• [2024.03]: our survey on Domain Speciliazation of LLM is honorably mentioned by the 2024 Economic Report of the President from the White House.
• [2024.02] Our new paper on analyzing LLM behavior on graph recall from human cognition perspective is now online. Check it out here!
• [2024.01] We will be conducting a new tutorial for BrainGB at the ISBI 2024 conference in Athens, Greece at the end of this May.
• [2024.01] An extended abstract is accepted to SPIE Medical Imaging 2024 (Oral).
• [2023.12] Glad to received NSF Student Travel Support Award for the ICDM 2023.
• [2023.09] Our paper on artificial node features for GNNs has been consistently ranked as 1st in the 3 consecutive lists of Most Influential CIKM Papers produced by Best Paper Digest ( 2023-01, 2023-04, 2023-09).
• [2023.09] One paper on visual knowledge extraction is accepted to NeurIPS'23.
• [2023.09] Two papers are accepted to PSB'24. Congrats to Alexis (High-Schooler)!
• [2023.08] Humbled to be selected as a Rising Star in EECS this year!
• [2023.06] Our review paper on healthcare knowledge graph is now online.
• [2023.05] One collaborative paper on biological data augmentation is accepted to KDD'23.
• [2023.05] One paper on multimodal extraction is accepted to ACL'23 Findings.
• [2023.04] Our paper on GNN pre-training on brain networks is accepted to CHIL'23 (Oral).
• [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.
• [2022.09] One collaborative paper on transformer is accepted to NeurIPS'22 (Spotlight).
• [2022.08] One paper on GNN node feature choices 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).