Centers

Applied Statistics Center

The Applied Statistics Center (ASC) is a community of scholars at Columbia organized around research projects in the human, social, and engineering sciences, as well as basic statistical research. In addition to coordinating existing projects and seminars, the Center supports visitors and research fellows, facilitates the development of new projects, and connects Columbia students in statistics and quantitative social science as part of research teams in data-rich projects, providing topics for M.A. and Ph.D. theses.

Center for the Study of Development Strategies

The Center for the Study of Development Strategies (CSDS) provides a forum at Columbia to support rigorous field based research on major questions in the political economy of development. Research at the center focuses on democracy and governance, peacebuilding, and aid effectiveness. The center is supported by the Earth Institute, ISERP, and the Political Science department at Columbia.

Center for the Study of Wealth and Inequality

The Center for the Study of Wealth and Inequality (CWI) takes as its mission the investigation of income and wealth, along with exploring the dimensions of societal inequality in these household resources. The Center's interests encompass issues of poverty, labor market behavior, public transfer programs and tax policy, in that each has a clear relevance to economic inequality, family resources, and to living standards.

Center on African American Politics and Society

The Center on African American Politics and Society (CAAPS) provides an intellectual infrastructure for social science research on the political, social, and economic conditions affecting black communities. It aims to support theoretically sophisticated and policy-informed research among Columbia faculty, using a variety of methods and approaches that intersect various disciplines, including political science, psychology, sociology, law, economics and urban studies.

Center on Organizational Innovation

The Center on Organizational Innovation (COI) promotes research on organizational innovation as well as new forms of collaboration, communication, and coordination made possible with the advent of interactive technologies.

Columbia Experimental Laboratory for the Social Sciences

The Columbia Experimental Laboratory for the Social Sciences (CELSS) has opened at Columbia. CELSS resides on the 5th floor of the International Affairs Building and is an interdisciplinary venue for researchers in Economics, Political Science, Sociology, SIPA and the Business School. It has 24 computers for participants and one computer for the experimenter. The goal is to enable students and faculty to run laboratory experiments in a controlled setting.

Columbia Justice Lab

The Justice Lab combines original research, policy development, and community engagement to propel the project of justice reform. In our vision, justice depends on peaceful and healthy communities that help all their members to flourish in a climate of fairness and respect. We work for a community-centered justice, in which incarceration is no longer used as a solution to problems that are often rooted in poverty and racial inequality.

Columbia Program on Indian Economic Policies

The Program on Indian Economic Policy (PIEP) is funded by a generous grant from the Templeton Foundation and brings together scholars from Columbia and other universities and think tanks around the world. The program houses a data center on India’s economy and organizes lectures, seminars, and conferences in the U.S. and India.

The AI Model Share Project

The AI Model Share Project is a newly funded academic center at Columbia University. Its mission is to generate the tools needed to assist students, faculty, and the wider data science community to bring machine learning innovations to all manner of end-users. The initiative received Start Up Center grant funding from ISERP in July of 2019 to build a platform (Python library + integrated website) that will act as the world's trusted academic repository for machine learning model prediction APIs.

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