A Wide Umbrella

The Data Science Institute connects Temple University Centers of Excellence with a focus on data science research initiatives. The Institute is comprised of several Centers, each with a specific multi-disciplinary perspective and unique focus. These centers also bridge Fox School programs with those from the College of Science and Technology and the School of Medicine. This dynamic infrastructure is designed to engage new Centers and faculty across the Temple University campus as the demand for big data analytics continues to flourish.

The Institute adopts a dynamic and inclusive model that encourages participation from all departments and schools at Temple University. Starting with several centers in the College of Science and Technology, the School of Medicine, and the Fox School of Business – the long term goal is expand this reach by engaging other units, including Fox Chase Cancer Center, School of Engineering, School of Media and Communications, and College of Health Professions and Social Work, plus other colleges/schools that are active in research centered on big data, data sciences, and data analytics.


The Data Science Institute at Temple University aims to become a global leader in research, education, industry practice, and technology transfer in the inter-disciplinary domain of data science by pushing the frontiers of science, engineering, and social sciences.


The mission of the Data Science Institute is to foster inter-disciplinary collaboration in data sciences across Temple University and act as a catalyst for academic, practice-oriented, and translational research to pursue academic discovery, offer educational opportunities, support entrepreneurial ventures and commercialization opportunities, inform industry, and help society at large by exploring the value and potential of data science.

Specific Objectives

  • Forge relationships among faculty and students within and outside Temple University to facilitate inter-disciplinary research in the domain of data science and data science analytics.
  • Stimulate and enable new inter-disciplinary collaborations in data mining, dimensionality reduction, predictive modeling, optimization, algorithms, and computational methods.
  • Enable exploratory research on data sciences and analytics to advance the field of big data by developing new methods for extracting knowledge and understanding patterns in data.
  • Develop and deliver educational initiatives in the domain of big data to support the next generation of data scientists for academia and practice.
  • Implement inter-disciplinary curricula at the graduate and undergraduate level to train the next generation of professions in the data analytics and data sciences.
  • Develop government and industry partnerships for research, education, and training.
  • Build alliances with industry partners to promote beneficial relationships in tackling practical problems related to data science.
  • Seek to commercialize its technology, methods, and patents related to data science to deliver solutions that will benefit industry and society at large.
  • Develop the infrastructure to support research and education in the areas of data mining, computation, data analytics, and data visualization.
  • Develop outreach programs to the community by creating new opportunities from big data.
  • Leverage existing partnerships with industry to translate academic and theoretical contributions into real-world applications for industry and society.
  • Support a small numbers of new “Centers of Excellence” in the domain of data science.