MIDAS will create and maintain a thriving community in data science on the U-M campus in the service of its University of Michigan stakeholders and of emerging national needs. MIDAS will oversee and lead Data Science Challenges in four initial areas (Transportation Research, Learning Analytics, Personalized Medicine and Health, and Social Science). It will build a critical mass of data science faculty to foster a collaborative cross-cutting methodological and applied research community in data science. MIDAS will lead and coordinate next generation data science education and training; engage industry in data science at U-M; and promote usage of data science services and infrastructure on the U-M campus.

Strategic Goals

  1. Invigoration: of U-M data science research in methodology and its application
  2. Development: of new programs/schools/workshops in data science education
  3. Enhancement: of U-M visibility in data science through web presence, visiting scholars program, seminars, workshops and summer schools, and major extramural sponsored research initiatives
  4. Partnership and Collaboration: between methodologists and practitioners, academia and industry, academia and government
  5. Integration: of methodology, computational infrastructure, and consulting services