Xihong Lin
Papers
1
Total Citations
4
H-Index
1
About
Xihong Lin is a leading biostatistician whose research bridges statistical methodology, genetic epidemiology, and health outcomes. She is renowned for developing innovative statistical methods for analyzing high-dimensional genomic data, particularly in genome-wide association studies (GWAS) and sequencing studies. Her seminal contributions include the SKAT (Sequence Kernel Association Test) framework, a powerful tool for detecting rare variant associations, which has been cited over 4,000 times and is widely used in human genetics. Lin’s work also advances mixed models, survival analysis, and statistical learning for complex biomedical data, with applications in cancer research and precision medicine. With over 40,000 total citations and an H-index exceeding 80, she has profoundly shaped modern biostatistics. A member of the National Academy of Medicine and a Harvard University professor, Lin’s research empowers scientists to uncover genetic underpinnings of disease, improving public health. Her impact extends to mentoring the next generation of statisticians and leading collaborative studies on cancer outcomes, making her a transformative figure in quantitative biology.
Research Focus
Key Achievements
Top Papers
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