John Palowitch

I’m a Quantitative Analyst at Google. In 2017 I received my Ph.D. in Statistics from the Department of Statistics and Operations Research (STOR) at UNC Chapel Hill. My research interests include machine learning and statistical methods for networks, and computational genomics. My thesis work was under the advisement of Andrew B. Nobel and Shankar Bhamidi. Since May 2014, I have been part of a working group in the GTEX Project. (This affiliation is maintained unofficially now that I have joined Google.) I was part of the Probability Group at UNC.

Info about the Continuous Configuration Model Extraction (CCME) method can be found at the menu link above. The implementation of the ACME method for eQTL effect-size is documented here.

CV: John Palowitch Curriculum Vitae // Google Scholar // github. My email:



  1. Aguet, Francois; …; Palowitch, John; Wright, Fred A.; GTEx Consortium; Lappalainen, Tulli; Ardlie, Kristin G.; Dermitzakis, Emmanouil T.; Brown, Christopher D.; Montgomery, Stephen D. “Local genetic effects of gene expression across 44 human tissues.” bioarXiv link [in publication at Nature Genomics]
  2. Palowitch, John; Zhou, Yihui; Shabalin, Andrey; Zhou, Yihui; Nobel, Andrew B.; Wright, Fred A. “Estimation of Interpretable eQTL Effect Sizes Using a Log of Linear Model.” arXiv link [in publication at Biometrics]
  3.  Palowitch, John; Bhamidi, Shankar; Nobel, Andrew B. “Significance-based community detection in weighted networks.” arXiv link / supplemental doc [in revisions at Journal of Machine Learning Research]
  4. Jiang, Melei; Palowitch, John; Yu, Qunqun; Marron, J. S.; Haaland, Perry D. “Finding Community Subtypes in the Microbiome of the Infected Lower Lung.” [in preparation]
  5. Wilson, James D.; Palowitch, John, Bhamidi, Shankar; Nobel, Andrew B. “Significance Based Extraction in Multilayer Networks with Heterogeneous Community Structure” arXiv link [in publication at Journal of Machine Learning Research]

Conferences and Presentations