Research Centers in the Field of Data Science
Center for Data Science (CDS)
The NYU Center for Data Science (CDS) is a focal point for New York University’s university-wide initiative in data science. It was established to help advance NYU’s goal of creating the country’s leading data science training and research facilities, arming researchers and professionals with tools to harness the power of big data.
Center for the Promotion of Research Involving Innovative Statistical Methodology (PRIISM)
The Center for the Promotion of Research Involving Innovative Statistical Methodology (PRIISM) is a new center dedicated to improving the caliber of research in quantitative social, educational, behavioral, allied health and policy science.
Center for Urban Science and Progress (CUSP)
The Center for Urban Science and Progress (CUSP) is a unique public-private research center offering educational programs in applying big data to issues of urban life and infrastructure. CUSP is backed by the support and cooperation of New York City.
NYU Center for Genomics and Systems Biology
The mission of the Center for Genomics and Systems Biology is to define how regulatory networks operate and how they have evolved to generate diversity across species. For this work, we use approaches that span systems biology, comparative functional genomics and bioinformatic analysis focusing on model organisms and phylogenetically related species.
NYU Center for Health Informatics and Bioinformatics (NYU Langone Medical Center)
The mission of CHIBI is to catalyze transformative changes in biomedicine through breakthrough computational methodological research, best practices services, state of the art infrastructure and cutting-edge education.
Stern Center for Business Analytics (CBA)
The Center for Business Analytics (CBA) at the Stern School of Business is an interdisciplinary community at the forefront of data and analytical thinking.
Departments Engaged in Data Science
Department of Computer Science, Courant Institute
The Department of Computer Science has considerably expanded over the past few years, adding many outstanding faculty with diverse research interests. The Department’s research areas include computational biology, machine learning and knowledge representation, and scientific computing.
Department of Economics, Arts and Science
In the 1990s and early 2000s, the Department of Economics at New York University evolved into one of the world’s leading centers for research and teaching in economics. Research activities include econometrics, macroeconomics, finance and monetary economics.
Department of Information, Operations & Management Sciences (IOMS), NYU Stern
The Department of Information, Operations & Management Sciences (IOMS) is a common home to faculty whose research style is analytical or technology-based. Three Groups — Information Systems, Operations Management and Statistics — combine their strengths and capabilities in IOMS.
Department of Mathematics, Courant Institute
The Department of Mathematics at the Courant Institute is a center for training and research in the mathematical sciences. Its special character includes a large permanent faculty specializing in overlapping areas throughout pure and applied mathematics, scientific computation and computer science.
Department of Physics, Arts and Science
The Department of Physics includes applied math, biophysics, and statistical and mathematical physics.
Department of Sociology, Arts and Science
The Department of Sociology emphasizes both theoretical creativity and substantive empirical research on important social issues. It encourages a range of analytic perspectives and maintains strength in both quantitative and qualitative methods.
Division of Biostatistics, Department of Population Health, Medical Center
Biostatistics is a scientific discipline that focuses on study design and collection, analysis, and interpretation of data to improve human health. The Division of Biostatistics is the academic home of faculty who contribute to scientific advances that benefit human health through innovation in methodology, theory, and application of biostatistical methods across the entire spectrum of biomedical research.