Faculty Profile

Hae Kyung Im
Section of Genetic Medicine
Assistant Professor of Medicine

Academic Interests

Dr. Im's research centers on developing statistical methods to sift through the vast amounts of genomic and other high dimensional data to understand the biological mechanisms that drive complex diseases with the ultimate goal of making discoveries that can be translated into improving the health of people. She focuses on methods that predict and dissect complex traits using data from multiple heterogeneous sources. For example, she has proposed a prediction method called OmicKriging that integrates data from heterogeneous sources to improve prediction performance. She has also used the prediction of intermediate phenotypes as an instrument to probe the mechanisms that link genetic variants with complex diseases and traits. This is implemented in two related methods called PrediXcan and MetaXcan. Her methods, software, and results are open to the public to promote open and reproducible science.

Clinical Interests



  • E. R. Gamazon, H. E. Wheeler, K. P. Shah, S. V. Mozaffari, K. Aquino-Michaels, R. J. Carroll, A. E. Eyler, J. C. Denny, GTEx Consortium, D. L. Nicolae, N. J. Cox, and H. K. Im, “A gene-based association method for mapping traits using reference transcriptome data.,” Nat Genet, vol. 47, no. 9, pp. 1091–1098, Sep. 2015.
  • GTEx Consortium, “The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans.,” Science, vol. 348, no. 6235, pp. 648–660, May 2015.
  • H. E. Wheeler, K. Aquino-Michaels, E. R. Gamazon, V. V. Trubetskoy, M. E. Dolan, R. S. Huang, N. J. Cox, and H. K. Im, “Poly-Omic Prediction of Complex Traits: OmicKriging.,” Genetic epidemiology, May 2014.
  • H. K. Im, E. R. Gamazon, D. L. Nicolae, and N. J. Cox, “On sharing quantitative trait GWAS results in an era of multiple-omics data and the limits of genomic privacy.,” Am J Hum Genet, vol. 90, no. 4, pp. 591–598, Apr. 2012.
  • H. K. Im, E. R. Gamazon, A. L. Stark, R. S. Huang, N. J. Cox, and M. E. Dolan, “Mixed effects modeling of proliferation rates in cell-based models: consequence for pharmacogenomics and cancer.,” PLoS Genetics, vol. 8, no. 2, p. e1002525, Feb. 2012.
For a complete list of publications click here:


  • MS, 1993, Balseiro Institute, Argentina, Physics
  • MS, 2000, University of Chicago, Financial Mathematics
  • PhD, 2005, University of Chicago, Statistics