Summary
Yunguan Wang is an assistant professor and bioinformatics scientist with nine years of experience applying machine learning, multi-omics integration, and big-data mining to translational problems in drug discovery and spatial single-cell biology. He has built deep learning and latent-graph models for image and spatial transcriptomics denoising, designed large analysis pipelines that uncovered drivers in prostate cancer, translocation RCC, and SARS-CoV-2 immune responses, and led computational screens that prioritized small molecules for cystic fibrosis. His work bridges algorithm development and wet-lab validation—screening over a million L1000 profiles to nominate compounds that restored CFTR function—demonstrating an uncommon end-to-end competence from model to experiment. Based in Ohio, he combines PhD-level bioinformatics training with practical data science roles at leading institutions (Harvard, UT Southwestern, Cincinnati Children’s), consistently translating high-dimensional data into testable biological hypotheses.
10 years of coding experience
9 years of employment as a software developer
Doctor of Philosophy - PhD, Bioinformatics, Doctor of Philosophy - PhD, Bioinformatics at University of Cincinnati College of Medicine
B.E., Bioengineering, B.E., Bioengineering at Dalian University of Technology
English, Chinese