Zhenbang Wu
- University of Illinois Urbana-Champaign
- Ph.D. Candidate in Computer Science
- zw12@illinois.edu
I am a Ph.D. candidate in Computer Science at the University of Illinois Urbana-Champaign. I am fortunate to be advised by Prof. Jimeng Sun. Before this, I received dual bachelor’s degrees from Zhejiang University and the University of Illinois Urbana-Champaign.
[Research] My research focuses on developing robust foundation models (e.g., large language models and multimodal models) for healthcare and drug discovery applications. The core of my work involves addressing various distribution shifts between training and testing data, encompassing challenges like missing modalities, covariate shift, and the emergence of new labels.
[Application] I co-lead the development of PyHealth, an open-source toolkit for predictive modeling with multimodal clinical data. It has received over 800 stars and 20K downloads on GitHub.
News
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Jan 2024: Our paper “Multimodal Patient Representation Learning with Missing Modalities and Labels” is accepted by ICLR 2024!
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Sep 2023: Our paper “An Iterative Self-Learning Framework for Medical Domain Generalization” is accepted by NeurIPS 2023!
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Jun 2023: I will join NIH for the summer internship.
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Jun 2023: Our paper “MedLink: De-Identified Patient Health Record Linkage” is accepted by KDD 2023!
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May 2023: Our software “PyHealth” is accepted by KDD 2023 Hands-on Tutorial Track!
Publications & Preprints (Google Scholar)
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Multimodal Patient Representation Learning with Missing Modalities and Labels
ICLR 2024 Zhenbang Wu, Anant Dadu, Nicholas Tustison, Brian Avants, Mike Nalls, Jimeng Sun, Faraz Faghri [paper] -
An Iterative Self-Learning Framework for Medical Domain Generalization
NeurIPS 2023 Zhenbang Wu, Huaxiu Yao, David M Liebovitz, Jimeng Sun [paper] -
MedLink: De-Identified Patient Health Record Linkage
KDD 2023 Zhenbang Wu, Cao Xiao, Jimeng Sun [paper] -
PyHealth: A Deep Learning Toolkit For Healthcare Applications
KDD 2023 Hands-on Tutorial Chaoqi Yang*, Zhenbang Wu*, Patrick Jiang, Zhen Lin, Junyi Gao, Benjamin Danek, Jimeng Sun [paper] -
MedCLIP: Contrastive Learning from Unpaired Medical Images and Text
EMNLP 2022 Zifeng Wang, Zhenbang Wu, Dinesh Agarwal, Jimeng Sun [paper] -
AutoMap: Automatic Medical Code Mapping for Clinical Prediction Model Deployment
ECML-PKDD 2022 Zhenbang Wu, Cao Xiao, Lucas M Glass, David M Liebovitz, Jimeng Sun [paper] -
Knowledge-Driven New Drug Recommendation
Preprint (short version presented in the NeurIPS 2022 Workshop on Meta-Learn) Zhenbang Wu, Huaxiu Yao, Zhe Su, David M Liebovitz, Lucas M Glass, James Zou, Chelsea Finn, Jimeng Sun [paper]
Softwares
Internship Experiences
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National Institutes of Health, Bethesda, MD, USA
Machine Learning Research Intern, with Dr. Faraz Faghri & Dr. Mike Nalls
Multimodal learning
May 2023 - Present
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IQVIA, Remote, USA
Machine Learning Research Intern, with Dr. Lucas M Glass
Patient record linkage
May 2022 - Aug 2022