Yu Huang
Tenure-track Assistant Professor · Biostatistics and Health Data Science
Indiana University School of Medicine
AI that turns real-world health data into fair, actionable evidence.
I'm a tenure-track Assistant Professor in the Department of Biostatistics and Health Data Science at Indiana University School of Medicine, an Investigator at the Regenstrief Institute's Clem McDonald Center for Biomedical Informatics, and an Adjunct Professor in Purdue University's Weldon School of Biomedical Engineering. I develop machine learning methods for electronic health records, medical images, and other real-world data: to model how diseases progress, to find patient subgroups, and to make sure the resulting models work fairly for everyone.
Before IU, I was a postdoctoral associate with Jiang Bian at the University of Florida. I received my Ph.D. in Computer Science from National Yang Ming Chiao Tung University in 2022, co-advised by Vincent S. Tseng and Gary G. Yen.
Research
What I work on
Fair machine learning
Risk models that stay accurate and equitable across patient groups when they learn from real-world data.
Read more 02Disease subphenotyping and prediction
Graph and sequence models that find progression subtypes in EHRs and physiological signals and predict outcomes early.
Read more 03Health digital twins
Patient-level computational models that forecast how health will change and test what-if treatment scenarios.
Read more 04Retinal imaging
Foundation models and interpretable learning for OCT and fundus images, including the eye as a window on dementia risk.
Read moreNews
Recent updates
- Sep 2026Joined the NIH-funded AI-Powered Coordinating Center (AICC) for the NIA AITC Program on Aging and AD/ADRD Research as senior/key personnel.
- Aug 2026Presented MedCausalAtlas, which builds literature-derived causal DAGs for clinical evidence synthesis, at ACM SIGKDD 2026 in Jeju, Korea.
- 2026Selected as a semi-finalist in the Grand Prize Phase of the NAM Healthy Longevity Global Competition.
- 2026Welcomed postdoctoral associates Zhaohui Wang and Hao Xuan.
- 2026Serving as chair of the Health Data Challenge (2026) and the Analytics Track (2027) at the IEEE Conference on Health Informatics.
- 2026Temporally Detailed Hypergraph Neural ODE for Disease Progression Modeling was accepted at ICLR 2026.
Earlier news
- 2026Identifying Alzheimer’s disease progression subphenotypes via a graph-based framework was published in Journal of Healthcare Informatics Research.
- Nov 2025Appointed adjunct professor in the Weldon School of Biomedical Engineering at Purdue University.
- 2025Received a Catalyst Award in the NAM Healthy Longevity Global Competition.
- 2025Received pilot funding from IU Lab.
- Feb 2025Joined Indiana University as a tenure-track assistant professor in Biostatistics and Health Data Science, and the Regenstrief Institute as an investigator.
- 2025From Image to Report, on automating lung cancer screening reports with vision-language models, was published in Journal of Biomedical Informatics.
- 2025Optimizing Strategy for Lung Cancer Screening was published in JCO Clinical Cancer Informatics.
- 2024A fair individualized polysocial risk score for identifying increased social risk in type 2 diabetes was published in Nature Communications.
Publications
Selected papers
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A fair individualized polysocial risk score for identifying increased social risk in type 2 diabetes
Nature Communications, 15(1), 8653, 2024
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Temporally Detailed Hypergraph Neural ODE for Disease Progression Modeling
The Fourteenth International Conference on Learning Representations (ICLR), 2026
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Journal of Healthcare Informatics Research, 10(2), 317–339, 2026
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Adaptation of a fair individualized polysocial risk score for hospitalization risk prediction
JAMIA Open, 9(4), ooag161, 2026
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Snippet Policy Network for Multi-class Varied-length ECG Early Classification
IEEE Transactions on Knowledge and Data Engineering, 35(6), 6349–6361, 2022
Work with me
Recruiting Ph.D. students and postdocs
I'm looking for people who want to build AI methods for real-world health data, including EHRs, medical imaging, and multimodal data, with a focus on fairness, disease progression, and digital twins. Email me your CV and a short note on what you'd like to work on.