Tai-hsien Yang
Research Scientist at Columbia University
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolTai-hsien Yang is a research scientist and strategic data science leader with 13 years of experience applying multi-omic and machine learning methods to accelerate drug discovery from preclinical research through Phase 2 clinical trials. He has deep expertise in bulk and single-cell RNA-seq analytics and a track record of translating complex biological questions into productized analytics and biomarkers. At Roche he co-led global single-cell and multi-omics networks, building and scaling teams of 50+ scientists to deliver hundreds of analytics impacts across early R&D, and he now continues that work in academia at Columbia. He has implemented LLM-based solutions to democratize data access for scientists, blending rigorous engineering with translational insight. Trained as an electrical engineer (PhD, Columbia) with top academic performance, he pairs quantitative depth with practical leadership across industry and academic settings.
13 years of coding experience
8 years of employment as a software developer
Bachelor, Mechatronics, 3.98/4.00, Bachelor, Mechatronics, 3.98/4.00 at National Taiwan UniversityDoctor of Philosophy - PhD, Electrical and Electronics Engineering, Doctor of Philosophy - PhD, Electrical and Electronics Engineering at Columbia University in the City of New York
English, Chinese
Github Skills (6)
rna-seq5
bioinformatics2
python2
velocity2
rna-velocity1
javascript1
Programming languages (1)
Github contributions (5)
th86/transmeddatasets
Apr 2017 - Feb 2018
Contributions:30 commits, 28 pushes, 1 branch in 10 months
th86/gislkit
Jun 2014 - Oct 2018
Contributions:50 commits, 30 pushes in 4 years 4 months
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