
I'm an Assistant Professor of Applied Statistics in the department of Applied Statistics, Social Science, and Humanities (ASH) at New York University's Steinhardt School, with an affiliated appointment at New York University's Center for Urban Science and Progress (CUSP). I am an affiliated researcher at the Stanford Computational Policy Lab, and a member of the Machine Learning for Good Lab at NYU.
Previously I was a Senior Research Scientist at CUSP and a 2016-2017 fellow at the Data & Society Research Institute. Before that I was a postdoc in the Mathematical Sciences Institute at the Australian National University. I studied mathematics at UC San Diego (M.S. and Ph.D.), applied urban science and informatics at CUSP (M.S.), and mathematics and economics at the University of Washington (B.S.). Additional details are in my CV.
My research interests are broadly related to computational social science, and in particular the application of statistical and machine learning methods to a variety of urban issues. Current research projects include the use of interpretable models to inform pretrial detention decisions, statistical techniques to accurately measure gunfire-related crime, and predictive models in child welfare.
Previously I was a Senior Research Scientist at CUSP and a 2016-2017 fellow at the Data & Society Research Institute. Before that I was a postdoc in the Mathematical Sciences Institute at the Australian National University. I studied mathematics at UC San Diego (M.S. and Ph.D.), applied urban science and informatics at CUSP (M.S.), and mathematics and economics at the University of Washington (B.S.). Additional details are in my CV.
My research interests are broadly related to computational social science, and in particular the application of statistical and machine learning methods to a variety of urban issues. Current research projects include the use of interpretable models to inform pretrial detention decisions, statistical techniques to accurately measure gunfire-related crime, and predictive models in child welfare.