Christina Freyman is an evaluator at the National Science Foundation. At NSF, she employs various algorithmic techniques to obtain evidence for decision making from NSF’s administrative data systems, including the measurement of partnerships and broader impacts in the NSF portfolio.  She also oversees or supports various evaluation and monitoring projects related to federal government investment in R&D. Prior to joining NSF, she was the principal investigator on grants related to advanced analytics, big data, and metrics related to evaluation. She has also conducted mixed methods evaluations of government sponsored R&D with quantitative economic analyses and program evaluation tools including machine learning-based text analysis and bibliometric analyses.  Dr. Freyman has a Ph.D. in materials science and engineering from Northwestern University and a M.P.P. from the University of Chicago.