To train a diverse group of Ph.D. students in the latest Big Data empirical research methodologies in Macro-Finance

To support a symposium evaluating the state of science and technology in the US and the policies that will support its future development

To produce an interdisciplinary white paper on differential privacy and the Census

To quantify the impact of differential privacy on the utility and accuracy of Decennial Census data for social science research

To support a special semester of research on lattice methods for fully homomorphic encryption and on applications for privacy-preserving computations on confidential data

To assess how the privacy and accuracy of social science research will be affected by new disclosure-avoidance algorithms governing the release of 2020 Census data

To support plans to improve government administrative data linkages that would enhance social science research

To develop a community of data experts that help federal agencies with data-driven decision-making andКdata-policy implementations

To develop articles and resources that highlight uses of the Decennial Census and other data produced by federal statistical agencies

To develop and test algorithms based on Bayesian and Machine Learning techniques for efficient entity resolution when linking datasets