Ran Zhang

I am a UW Data Science postdoctoral fellow with Dr. William Noble at the University of Washington. My work is supported by the NIH Pathway to Independence Award from NHGRI. Before this, I did my undergraduate studies at Tsinghua University and my graduate studies at Princeton University, supervised by Dr. Olga Troyanskaya.

In July 2025, I will start my independent lab at the School of Data Science and Society, UNC-Chapel Hill. I am looking for prospective PhD students and Postdocs interested in developing and applying machine learning methods to understand tissue/cellular regulations and complex human diseases. If you are interested, please email your CV, a short description (in than one page) of research interests to ranz0 at uw.edu

I started my career as a wet lab biologist in undergraduate studies. I used a combination of experimental approaches – including imaging, biochemistry, and cell biology – to study autophagy in human cell lines and yeast. My graduate work is focused on integrating large-scale functional genomics datasets and applying network-based approaches to predict context-specific disease genes and pathways in neurodevelopmental and neurodegenerative diseases and disorders. During my postdoc studies, I developed deep learning methods to integrate and translate single-cell multi-omics profiles across data modality, time, and species to generate biological hypotheses in biological contexts or data modalities where experimental measurement is scarce.

My research interests include:

Bulk and single-cell level cross-modality translation and integration
Cross-species prediction to transfer knowledge from model organisms to human
Characterizing genes and processes underlying complex human diseases, disorders, and conditions (e.g., Alzheimer’s disease, Autism spectrum Disorder, Turner Syndrome)