Nathan VanHoudnos is a senior machine learning research scientist at Carnegie Mellon University’s Software Engineering Institute. As a data scientist and applied statistician, VanHoudnos focuses on solving problems at the intersection of statistics, machine learning, and cybersecurity. In particular, he develops machine learning solutions for visualization, static analysis, threat analysis, and vulnerability analysis. He received a Ph.D. from Carnegie Mellon University in statistics and public policy, as well as M.S. degrees in public policy and management and statistics.
2014 Ph.D. in Statistics and Public Policy, Carnegie Mellon University
2012 M.Phil. in Public Policy and Management, Carnegie Mellon University
2010 M.S. in Statistics, Carnegie Mellon University
2005 B.S. in Mathematics and Physics, University of Illinois at Urbana-Champaign