Zach Kurtz is a machine learning research scientist at Carnegie Mellon University’s Software Engineering Institute. He has experience on projects in fields as diverse as cybersecurity, public transit, psychology, marketing analytics, ecology, medicine, human rights, and international capital flows. Kurtz’s dissertation built on capture-recapture theory to introduce a new method for estimating the sizes of partially observed populations. At the SEI, Kurtz has developed new evaluation methodologies for open-ended cyber warning competitions, built text-based classifiers, and designed cyber incident data visualization tools.


2014 Ph.D. in Statistics, Carnegie Mellon University

2007 M.S. in Applied Mathematics, University of Delaware

2005 B.S. in Mathematics, Eastern Mennonite University