Wenyu Zeng

Wenyu Zeng

she/her

PhD student in Biomedical & Health Informatics at the University of Washington. My research focuses on building scalable computational pipelines that integrate spatial transcriptomics and single-cell sequencing data to study glioblastoma heterogeneity. I’m passionate about combining biomedical data science and translational research to better understand tumor biology and identify therapeutic targets. Beyond research, I enjoy data visualization, teaching, and exploring new ways to make complex data accessible and meaningful.

Predicting COVID-19 Severity Levels Using Pre-COVID Metabolomic and Clinical Data

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This poster showed the several machine learning models being used to make a multi-level prediction on COVID-19 severity levels using patients’ pre-COVID metabolomic data. The output could further help guide clinical decisions for COVID-19 patients.