Kai Tang
Applied Statistician
West Lafayette, Indiana, United States
Summary
👤
Senior🎓
Top SchoolKai Tang is an applied statistician with a Ph.D. in computational biology and over a decade of experience turning large-scale NGS and epigenomics datasets into biological insight. With a strong joint MS in Statistics and Computer Science and 7 years working on high-performance supercomputing, he designs scalable pipelines and applies machine learning and statistical methods to plant genetics, DNA methylation, and histone modification studies. He has a proven publication record (40+ papers including Science and PNAS) and a track record of collaborating across academia and industry, currently applying his expertise at Inari. Beyond typical bioinformatics skills, Kai blends deep statistical rigor with practical HPC workflow engineering, enabling reproducible, high-throughput analyses in production settings.
12 years of coding experience
4 years of employment as a software developer
Bachelor of Science (B.S.) Life Science, Bachelor of Science (B.S.) Life Science at University of Science and Technology of ChinaMaster of Science - MS Statistics/Computer Science joint program, Master of Science - MS Statistics/Computer Science joint program at Purdue Universitytransfer to Purdue with lab Genetics Genomics and Bioinformatics Program, transfer to Purdue with lab Genetics Genomics and Bioinformatics Program at University of California, Riverside
Chinese, English
Github Skills (17)
r-package10
r10
shiny10
knitr10
rmarkdown10
bookdown10
gitbook5
markdown4
rstudio3
genetics2
computational-biology2
pipeline2
inference1
spectra1
throughput1
Programming languages (6)
Github contributions (5)
ktang/some_perl_code
Jan 2014 - Mar 2014
Contributions:8 commits in 2 months
ktang/perl_BS_code
Jan 2014 - Apr 2014
Contributions:10 commits in 2 months
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