I am a Clinical Associate Professor of Computer Science at the Courant Institute of New York University. At NYU in the fall of 2022, I am teaching Introduction to Computer Programming (in Python) and Data Management and Analysis. In the spring of 2023, I will be teaching those two courses again, as well as the graduate-level Database Systems course. I am also the faculty director for and an instructor in Courant’s Pathways to AI program, a summer program that introduces undergraduates to AI research.
My career has been focused on research and teaching in the areas of data science, artifical intelligence, machine learning, labor and education. In 2020, I was the lead instructor for a three cohorts of a 13-week data science intensive course designed to train students for careers as data scientists.
I am familiar with a wide range of statistical and machine learning algorithms, and I have extensive experience with large data sets, statistical analysis including regression analysis and propensity score matching, cluster analysis, database systems, and text processing. I am the author of a book on neural networks.
In my social science work, I have focussed on research and program evaluation in workforce development and training, labor markets, income security, and higher education.
At Abt Associates, I worked on a study for the U.S. Department of Labor that focused on analyzing the career trajectories of workers to see how these trajectories can inform the design of career pathway programs. I also worked on site impact studies for the Pathways for Advancing Careers and Education (PACE) randomized controlled trial (RCT) evaluation of career pathway programs for the U.S. Department of Health and Human Services (HHS). I was on the analysis team for the Green Jobs and Health Care evaluation, which also looked at career pathways programs. I am worked on the Career Pathways Intermediate Outcomes (CPIO) Study, which is HHS’s follow-on study for PACE and the related Health Profession Opportunity Grants (HPOG) study, as well as its follow-up study (HPOG 2), which are also sponsored by HHS. I applied techniques from machine learning to processing survey responses collected in these studies.
I was a principal investigator for Abt’s RCT for the Robin Hood College Success Prize, which measured the impacts of behavioral interventions delivered through smartphone apps on students at two community colleges. I have co-authored papers on the well-known I-BEST career preparation program in Washington State, on worker mobility over the course of the career (using social sequence analysis), on mobility within various industries in the service sector, and on progression in college. I have worked heavily with administrative data on educational and labor market outcomes, as well as with survey data. I have also published peer-reviewed articles that apply machine learning and data science to educational and labor market data.
On the technical side, I have experience with a wide range of specialized and general purpose programming languages, including Python (and Scikit-Learn), SQL, R, Stata, SAS, Perl, and Lisp. I have strong knowledge of and experience with the design, conduct, and analysis of experiments.
PhD in Computer Science
University of Wisconsin, Madison
PhD in Sociology
University of Wisconsin, Madison
BA in Physics (with Honors)