Our Mission

To strengthen University of Michigan’s preeminence in Data Science and to catalyze the transformative use of Data Science in a wide range of disciplines to achieve lasting societal impact.

Our Goals

  1. Community: Build a world-class data science community at U-M.
  2. Diversity and Inclusion: Ensure inclusion and promote diversity at all stages of the academic pipeline for data science, from high school students to organization leaders.
  3. Research: Catalyze and coordinate sustainable, multi-disciplinary and cutting-edge data science research.
  4. Education: Develop and support programs to educate the next generation of data science workforce, research leaders and citizens.
  5. Collaboration: Develop academic, industry, government and community partnerships in data science.
  6. Dissemination: Communicate UM data science accomplishments.
  7. Translation: Support the application of data science into impactful products, services, and policies, towards a better data-enabled society of tomorrow.

Our History

MIDAS has ~340 affiliate faculty from 16 schools and colleges at U-M Ann Arbor campus, and from U-M Dearborn and Flint campuses. Affiliate faculty members participate in MIDAS research and education events; are eligible for research and education programs designed for them; and contribute to the planning and implementation of MIDAS programs. MIDAS also hosts a large number of data science events, including research symposia, conferences, seminar series, and interdisciplinary brainstorming sessions. MIDAS also offers an online platform for constant engagement of the U-M data science community.  As the data science focal point at U-M, MIDAS collaborates with a diverse range of data science activities on campus.

Phase I of MIDAS research support featured the Challenge Initiative, which provided $10 million funding for projects in data-intensive transportation research, health science, social science, and learning analytics. MIDAS also launched the Data Science for Music program, with $300K of funding. MIDAS working groups are based on data science methodology and application themes, and catalyze cross-cutting research ideas and teams.  In Phase II of research support, MIDAS provides a number of programs that benefit the broad U-M data science community. These programs include grant proposal support and funding for high-impact and innovative research in data science theory, methodology, applications and societal impact.  

MIDAS brings attention to, and builds resources for, data science issues with broad implications, including data science ethics and research reproducibility. It organizes, with STATCOM, an annual symposium on Data Science for Good. It supports student data science teams, including one that performed ground-breaking work in Flint during the recent water crisis, using Data Science to predict the likelihood that a home had lead contamination in its water supply line.

MIDAS partners with multiple U-M departments, schools and colleges to offer a wide range of data science education options that span the entire talent development pipeline. MIDAS offers a postdoctoral Data Science Fellows program, a Graduate Certificate in Data Science program, a data science summer camp for high school students, and online classes. In addition, MIDAS is a partner in the U-M Master’s in Data Science program and undergraduate data science programs. MIDAS also sponsors student-led, faculty-mentored, data science teams, which carry out data science projects for community partners, non-profit organizations and industry sponsors, as well as participate in data science competitions.  MIDAS builds resources that allow students to carry out real-world data science projects that are embedded in the course offerings.

MIDAS actively engages industry, academic and community partners for both research and talent recruitment, with collaboration models that fit the goals of each partner. MIDAS has enabled joint research projects and large initiatives, with industry funding for U-M researchers from a few hundred thousand dollars to millions. MIDAS also has a Corporate Affiliate program that offers comprehensive support for talent recruitment. MIDAS faculty and students have collaborated with the cities of Detroit and Ann Arbor, as well as many other community and non-profit organizations to provide data science expertise. MIDAS is a member of the NSF Midwest Big Data Hub and provides leadership in several focus areas. MIDAS faculty leaders have participated in data science strategic planning at the national level through the National Academies of Science, Engineering and Medicine, NSF, and the advisory board at other universities. Internationally, MIDAS has developed formal collaboration relationship with Chinese University Hong Kong-Shenzhen and University College London.

Organizational Context

MIDAS is one component of the U-M Data Science Initiative that was launched in 2015. The Data Science Initiative brings together MIDAS and three other pre-existing units: Consulting for Statistics, Computing, and Analytics Research (CSCAR), Advanced Research Computing – technology Services (ARC-TS), and The Michigan Institute for Computational Discovery and Engineering (MICDE).

The idea of MIDAS started in 2012 when Drs. H.V. Jagadish and Vijay Nair organized discussions among faculty. They made an initial proposal to U-M leadership in 2014. Later in 2014, Drs. Jagadish and Brian Athey submitted the formal proposal to the Provost on behalf of a university-wide committee. In 2015, MIDAS was established with Drs. Athey and Alfred Hero as Co-Directors, and Drs. Jagadish and Nair as Distinguished Scientists and Co-Founders. Dr. Eric Michielssen, the then U-M Associate Vice President for Advanced Research Computing (ARC), was also instrumental in the creation of MIDAS. Drs. Hero and Athey completed their leadership terms at the end of 2018. Dr. Jagadish is the current Director.