Hi! I am a Postdoctoral Scholar at Stanford University Shah Lab. I received my Ph.D. in Computer Science and Informatics 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 focuses on large language model (LLM) evaluation and adaptation for healthcare. I am open to discussing research ideas and seeking academic collaborations. Drop me an email if interested!

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

• [2024.06] Our work on multi-agent LLM reasoning for EHR-based few-shot disease prediction is accepted to AMIA 2024 Annual Symposium. See you in San Francisco!
• [2024.06] Our work on multimodal instruction-tuning for biomedicine is online. Check it out.
• [2024.05] Our collaborative work on disease subtyping based on EHR data is accepted to SIGKDD Conference on Knowledge Discovery and Data Mining Applied Data Science Track.
• [2024.04] Our collaborative work on network recall by large language models is accepted to International Conference on Computational Social Science 2024 IC2S2'24 as an Oral.
• [2024.04] My PhD Work is selected to the CHIL Doctoral Symposium. Thank you CHIL!
• [2024.04] I successfully defended my dissertation. Officially, Dr. Cui!
• [2024.03] Our survey paper on LLM domain specialization is cited by the 2024 Economic Report of the President! This annual report is generated by the Council of Economic Advisers in the White House to present an overview of the nation’s economic progress and makes the case for the Biden-Harris Administration’s economic policy priorities.
• [2024.01] We will be conducting a new tutorial collaborativefor BrainGB at the ISBI 2024 conference in Athens, Greece at the end of this May.
• [2024.01] A collaborative work 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).