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

• [2024.09] Our work on clinician preference aligned synthetic instruction generation for visual instruction tuning is accepted to NeurIPS'24 Datasets and Benchmarks Track.
• [2024.09] Our work on network recall by large language models is accepted to NeurIPS'24 Research Track. Abstract version is presented on IC2S2'24 as an Oral.
• [2024.06] Our work on multi-agent LLM reasoning for EHR-based few-shot disease prediction is accepted to AMIA Annual Symposium.
• [2024.05] Our work on disease subtyping is accepted to KDD Applied Data Science Track.
• [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!
• [2023.12] Glad to received NSF Student Travel Support Award for the ICDM 2023.
• [2023.09] Our paper on artificial node features on non-attributed graphs has been selected as Most Influential CIKM Papers produced by Best Paper Digest.
• [2023.09] One work on visual knowledge extraction is accepted to NeurIPS'23.
• [2023.09] Two work are accepted to PSB'24. Congrats to Alexis (High-Schooler)!
• [2023.08] Humbled to be selected as a Rising Star in EECS!
• [2023.05] One work on biological data augmentation is accepted to KDD'23.
• [2023.05] One work on multimodal extraction is accepted to ACL'23 Findings.
• [2023.04] Our work on brain network pre-training is accepted to CHIL'23 as an Oral.
• [2022.11] Our paper on few-shot learning is accepted to AAAI'23 as an Oral.
• [2022.11] Glad to receive NeurIPS AI4Science Travel Award!
• [2022.10] Our Benchmark paper on Graph Neural Networks for brain networks has now been officially accepted to IEEE TMI.
• [2022.09] Our paper on brain transformer is accepted to NeurIPS'22 as an Spotlight.
• [2022.08] One paper on node feature for non-attributed graphs is accepted to CIKM'22.
• [2022.06] One paper on interpretable GNNs is accepted to MICCAI'22 as an Oral.