Faculty

 

	Peter Kraft Professor of Epidemiology Departments of Epidemiology and Biostatistics pkraft@hsph.harvard.edu Dr. Kraft’s research focus is statistical methodology in genetic epidemiology, including family-based and population-based case-control studies.  Current projects include methods to measure association between haplotypes of multiple tightly-linked markers and disease in matched case-control studies and to detect gene x gene and gene x environment interactions.
	Nan Laird Harvey V. Fineberg Professor of Public Health and Biostatistics Department of Biostatistics laird@hsph.harvard.edu Dr. Laird’s major research interest is the development of statistical methodology in four primary areas: statistical genetics, longitudinal studies, missing or incomplete data, and analysis of multiple informant data.  She has worked extensively in the Analysis of Family Based Studies in Genetics, and currently collaborates on genetic studies in BiPolar Disorder, Asthma, and Lung Disease.
	Christoph Lange Associate Professor Department of Biostatistics clange@hsph.harvard.edu Dr. Lange’s current research interests fall into the broad areas of statistical genetics and generalized linear models.  In the area of family-based association tests (FBATs), he has focused on the development of power calculations for family-based association studies, multivariate extensions of the FBAT statistic, FBATs for time-to-onset data, and approaches to handle the multiple testing problem in family-based studies.
	Liming Liang Assistant Professor Departments of Epidemiology and Biostatistics lliang@hsph.harvard.edu Dr. Liang’s research focuses on developing the computational and statistical tools required for understanding human genetic variation, with a particular focus on complex human diseases.  He is currently working in the areas of: analysis of gene expression and methylation data; new statistical approaches for the analysis of next-generation sequencing data; new statistical framework to maximize the utility of multiple related phenotypes and elucidate how genetic and epigenetic variants and their interaction with environmental factors involve in pathogenesis of complex diseases and traits; and a statistical model to integrate genome-wide eQTL/meQTL data with genome-wide association studies.
	Xihong Lin Professor of Biostatistics Department of Biostatistics xlin@hsph.harvard.edu Dr. Lin’s major statistical research interests lie in developing statistical methods for high-dimensional and correlated data.  She is particularly interested in developing statistical and computational methods for “omics” data in population-based studies, such as genetic epidemiology, genetic environmental sciences, and clinical studies.
	Giovanni Parmigiani Professor of Biostatistics Department of Biostatistics gp@jimmy.harvard.edu Dr. Parmigiani’s research interests include models and software for predicting who is at risk of carrying genetic variants that confer susceptibility to cancer; statistical methods for the analysis of high throughput genomic data; Bayesian modeling and computation; and statistical methods for complex medical decisions.
	Alkes Price Assistant Professor Departments of Epidemiology and Biostatistics aprice@hsph.harvard.edu Dr. Price’s research focuses on the development of statistical methods for uncovering the genetic basis of human disease, and on the population genetics underlying these methods.  Particular areas of interest include disease mapping in admixed populations, heritability of complex traits, and statistical methods for sequencing studies.