Gabriel Ruiz


ruizg @

Advisor: Qing Zhou

PhD Student, 2017-present

Brief Bio:

I am a PhD student doing algorithmic and theoretical work on graphical models and causal discovery using observational data with planned applications in bioinformatics. Some other interests include models for network and relational data, and broadly the intersection of machine learning and statistics. I received my B.S. in statistics from University of Calfornia, Riverside in 2017 and had the pleasure of working there with Dr. Subir Ghosh through the MARC U program.


From my undergraduate years:

  1. OA Vsevolozhskaya, G Ruiz, DV Zaykin. "Bayesian prediction intervals for assessing P-value variability in prospective replication studies." Translational Psychiatry, 2017. [link]
  2. OA Vsevolozhskaya, CL Kuo, G Ruiz, L Diatchenko, DV Zaykin. "The more you test, the more you find: The smallest Pvalues become increasingly enriched with real findings as more tests are conducted." Genetic Epidemiology, 2017. [link]
  3. S Ghosh, B Wales, G Ruiz. "Maximum Likelihood Versus Alternative Regularized Estimators for Logistic Regression Models." In Revision.


I have been a Teaching Assistant for Statistics 10-Introductory Statistics and Statistics 100A-Probability with Texas Hold 'Em Examples.

Some Other Experiences:

I had the pleasure of working for Dmitri Zaykin at the National Institute of Environmental Health Sciences in Research Triangle Park, North Carolina in Summer 2016. And in Summer 2017 I worked at Draper Laboratory in Cambridge, MA with the Perception and Localization group thanks to the GEM Consortium Fellowship. I was also involved with the Highlander Statistics Society, a student chapter of the American Statistical Association.

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