Associate Professor of Applied Statistics
Steinhardt School of Culture, Education, and Human Development
New York University
Jennifer Hill is Associate Professor of Applied Statistics at the Steinhardt School of Culture, Education, and Human Development.
Hill develops methods that help us answer the causal questions that are vital to policy research and scientiﬁc development. In particular, she focuses on situations in which it is diﬃcult or impossible to perform traditional randomized experiments, or when even seemingly pristine study designs are complicated by missing data or hierarchically structured data.
Most recently, Hill has been pursuing two major strands of research. The ﬁrst focuses on Bayesian nonparametric methods that allow for ﬂexible estimation of causal models without the need for methods, such as propensity score matching. The second pursues strategies for exploring the impact of violations of typical assumptions in this work that require that all confounders have been measured. Hill has published in a variety of leading journals including Journal of the American Statistical Association, American Political Science Review, American Journal of Public Health, and Developmental Psychology. Hill earned her Ph.D. in Statistics at Harvard University in 2000 and completed a postdoctoral fellowship in Child and Family Policy at Columbia University's School of Social Work in 2002.