Tao Yang
Principal Scientist at Ochre Bio
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolTao Yang is a translational data science and computational genomics leader with a decade of experience applying multi-omics, spatial and single-cell technologies, and AI/ML to accelerate precision medicine and therapeutic development. Currently driving RNA therapeutics validation and computational biology strategy in biotech, he has led cross-functional teams to deliver IND-enabling analytics, biomarker discovery, and predictive models across gene therapy, immuno-oncology, neurodegeneration, and inflammatory disease programs. Tao has hands-on experience with large spatial transcriptomics datasets (one of the largest Xenium analyses), long-read sequencing, SomaScan proteomics, and real-world EHR integration, enabling biospecimen-to-clinical outcome translation for patient stratification. He is an inventor and author of algorithms such as AdRoit and HiCRep and has a track record of turning computational methods into actionable clinical strategy. Trained in statistical genomics (PhD) and biostatistics, he blends rigorous quantitative expertise with practical drug-development impact.
9 years of coding experience
7 years of employment as a software developer
Master of Science - MS, Biostatistics, Master of Science - MS, Biostatistics at Drexel UniversityDoctor of Philosophy (Ph.D.), Bioinformatics and Genomics (Statistical Genomics Option), Doctor of Philosophy (Ph.D.), Bioinformatics and Genomics (Statistical Genomics Option) at Penn State UniversityBachelor of Science - BS, Pharmacy (Pharmacology option), Bachelor of Science - BS, Pharmacy (Pharmacology option) at China Pharmaceutical University
Chinese, English
Github Skills (11)
r-package10
bioconductor5
infer4
bioinformatics4
composition2
spatial-transcriptomics1
spatial1
single-cell-genomics1
transcriptomics1
architecture1
single-cell-analysis1
Programming languages (1)
Github contributions (5)
qunhualilab/hicrep
Jun 2017 - Feb 2020
R package to evaluate reproducibility of Hi-C data
Contributions:9 commits, 9 pushes, 56 branches in 2 years 9 months
TaoYang-dev/hicrep
Dec 2016 - Dec 2020
R package to evaluate the reproducibility of Hi-C data
Contributions:238 commits, 111 PRs, 193 pushes in 4 years
r-packageevaluaterstatsreproducibilityhi-c
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