معرفی
Huang Lin is an Assistant Professor of Biostatistics at the University of Maryland's Department of Epidemiology and Biostatistics, School of Public Health. His research focuses on statistical methodologies, machine learning, and causal inference applied to high-dimensional omics data in microbiome and metabolomics studies, with applications in cancer, HIV/AIDS, maternal and child health, and clinical trials. He holds a BS in Statistics and Chemistry from Xiamen University (China), a PhD in Biostatistics from the University of Pittsburgh, and completed a postdoc at NIH.
His academic work bridges bioinformatics and statistical innovation, addressing challenges in biomedical data analysis. Notably, he explores causal inference frameworks for infectious disease studies and develops machine learning tools for omics data integration. Recent collaborations include improving clinical trial methodologies in maternal health and HIV treatment efficacy.
While his listed publications emphasize materials science for solid oxide fuel cells, this may reflect a dual academic focus or potential data overlap. His academic profile highlights biostatistics expertise, with research trends in interdisciplinary applications of statistical models to biomedical problems. No awards are explicitly listed, though his work demonstrates impactful contributions to methodological advancements.
