Huang Lin is an Assistant Professor of Biostatistics at the University of Maryland with eight years of experience bridging academia, industry, and government research. Trained with a Ph.D. from the University of Pittsburgh and dual bachelor's in statistics and chemistry, he applies rigorous statistical methods and machine learning to oncology and multi-omics problems. His background includes leading statistical contributions to a phase 3 NSCLC filing at Roche, integrative biomarker discovery at Boehringer Ingelheim, and translational clinical research during a NIH visiting fellowship. He routinely uses survival models, random survival forests, propensity-score methods, and integrative multi-omics techniques (DIABLO, SNF, iCluster) to turn complex biological data into actionable insights. An active researcher with a Google Scholar profile and public code on GitHub, he combines reproducible analysis practices (R Markdown) with practical regulatory experience. Colleagues describe him as a life-long learner who thrives at the intersection of statistical innovation and clinical impact.
8 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Biostatistics, Doctor of Philosophy (Ph.D.), Biostatistics at University of Pittsburgh
Bachelor's degree, Statistics, Bachelor's degree, Statistics at Xiamen University
Contributions:2 releases, 49 commits, 43 pushes in 1 year 3 months
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Huang Lin - Assistant Professor at University of Maryland