Environments

Environments

We are working to catalyze a new era of research that enables interdisciplinary approaches to data-intensive discovery.

Changes in academia are required to more fully support data scientists who enable new data-driven discoveries. We aim to create new types of institutional environments in which these discoveries can take place.

Moore-Sloan Data Science Environments

Other Data Science Centers

Many other institutions have an interest in promoting and facilitating data-driven discovery in academia. Below is a list of those that align closely with the objectives of the Data Science Environment Partnership.

Note: Although certificate and undergraduate or master’s degree programs in data science are a critical component of academic data science, we focus here on programs that emphasize the use of data-driven approaches to active research. For international data science educational programs, see this curated list: github.com/ryanswanstrom/awesome-datascience-colleges.

Institution Center or Program
Caltech Center for Data Driven Discovery
Columbia University Data Science Institute
Johns Hopkins University Institute for Data Intensive Engineering and Science
Michigan State University Computational Mathematics, Science and Engineering
Princeton University Center for Statistics and Machine Learning
Rensselaer Polytechnic Institute Data Science Research Center
Stanford University Stanford Data Science Initiative
University of Chicago Computation Institute
University of Massachusetts Amherst Center for Data Science
University of Michigan MIDAS: Michigan Institute for Data Science
University of Rochester Goergen Institute for Data Science
University of Virginia Data Science Institute
University of Washington at Tacoma Center for Data Science
Harvard University Data Science Initiative