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Statistical Genetics/Genomics, Spatial Statistics and Modeling

YSPH researchers are at the cutting edge of developing statistical methodology to address challenging issues in public health, biology and medicine. A few notable areas that have driven methodology research include multi-omics data (e.g. genetics, genomics, proteomics and metabolomics), spatial data (e.g. infectious disease and GIS data), network analysis, among others. Yale is also at the forefront of public health modeling, providing policy makers and care delivery organizations data driven risk scenarios from which to make decisions.

2022 Neyman Memorial Lecture Video: “Genes, Brain, and Us”

Heping Zhang, the Susan Dwight Bliss Professor of Biostatistics at the Yale School of Public Health, gives the prestigious 2022 Neyman Memorial Lecture by the Institute of Mathematical Statistics (IMS) at its annual meeting in London, June 27-30, 2022. Given every three years, this is one of the highest honors in statistical societies. The Neyman Lecture highlights innovative work at the intersection of statistical theory and scientific research. The honor carries with it a hefty bit of prestige: Named after groundbreaking Polish statistician Jerzy Neyman, a founder of modern statistical inference, the lecture has been given by just over a dozen of the top researchers in the field. The IMS, a leading statistical society, also invited Zhang to contribute an article related to his lecture to its publications.

IMS Neyman Lecture: "Genes, Brain, and Us"

by Heping Zhang - June 29, 2022

Faculty of Interest