معرفی
Jean Morrison serves as the John G Searle Assistant Professor in the Department of Biostatistics at the University of Michigan School of Public Health, a position she assumed in 2020 following postdoctoral work at the University of Chicago and doctoral studies at the University of Washington. Her academic trajectory reflects deep specialization in statistical methodologies for complex biological systems.
Her educational foundation includes:
- PhD in Biostatistics, University of Washington (2016)
- BA in Mathematics, University of Chicago (2009)
Dr. Morrison's research centers on statistical genetics and genomics, with pioneering work in high-dimensional phenotype analysis (e.g., brain imaging, proteomics, and clinical trait clusters). She develops advanced causal inference frameworks, notably for Mendelian randomization with robust pleiotropy handling, and integrates empirical Bayes methodologies with deep learning for genomic applications. Her approach emphasizes biologically interpretable low-rank representations of genetic associations.
Recent publications (2022-2025) reveal escalating focus on multi-omics integration (genome, transcriptome, proteome), probabilistic fine-mapping of causal variants, and methodological refinements for Mendelian randomization. Her work increasingly addresses genetic pleiotropy complexity through factor analysis and develops computational tools like GWASBrewer for realistic simulation of genetic data.
No scientific awards are documented in available sources. Similarly, public records contain no details regarding student advising, research grants, or laboratory leadership.
