Hao Cheng is an Associate Professor of Quantitative Genetics at UC Davis with 11 years of experience applying genomics, phenomics, pedigree and other big data to improve prediction of complex traits across species. He develops and implements statistical models and computational algorithms—spanning genomic prediction and GWAS—to translate theoretical quantitative genetics into scalable software for routine analysis of large datasets. His work bridges rigorous methodological research with hands-on tool development and practical application to diverse traits in agricultural and biological systems. Trained with a Ph.D. co-majoring in Genetics and Statistics from Iowa State, he combines deep statistical expertise with domain knowledge in genetics. Based in Davis, California, Hao is noted for turning advanced models into usable pipelines that support decision-making in breeding and research programs. An uncommon strength is his consistent focus on end-to-end solutions that move from theory to production-ready software for real-world genomic data.
11 years of coding experience
12 years of employment as a software developer
Doctor of Philosophy (Ph.D.), co-major in Genetics and Statistics, Doctor of Philosophy (Ph.D.), co-major in Genetics and Statistics at Iowa State University
Bachelor's degree, Genetics, Bachelor's degree, Genetics at China Agricultural University
Contributions:1 PR, 153 pushes, 2 branches in 5 years 10 months
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