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MIDAS Seminar

U-M Data Science Annual Symposium 2020

Keynote Speakers: Catherine D'ignazio and Lauren KleinCatherine D'ignazio Assistant Professor, Urban Science & Planning - Lauren Klein Associate Professor, English Quantitative Theory and Methods Emory University
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CALL FOR PRESENTATIONS

The Michigan Institute for Data Science (MIDAS) invites submission of 1) abstracts for presentations and 2) proposals for workshops, for the 2020 U-M Data Science Symposium.

As the focal point of data science at U-M, MIDAS facilitates the work of the broad U-M data science community, advances cross-cutting data science methodologies and applications, promotes the use of data science to benefit society, builds data science training pipelines, and develops partnerships with industry, academia and community.  The annual symposium showcases the breadth and depth of U-M data science, shares research ideas that will lead to the next breakthroughs, and builds collaboration.

Presentations at the symposium should cover one or more of the following areas of data science:

    • Theoretical foundations
    • Methodology and tools
    • Real-world application in any domain
    • The ethics and societal impact of data science
    • Emerging areas of data science

WE INVITE SUBMISSIONS FOR THE FOLLOWING:

1. Proposals for mini-workshops.  New this year, the symposium will include  3-5 mini-workshops on the afternoon of Nov. 10 as parallel sessions.  Each workshop will be two hours long and for 50-100 attendees.  They can be research discussion sessions, tutorials or hack sessions.  Proposals should include the theme, format, organizer and potential presenters, as well as how the proposed mini-workshop brings out the strengths across multiple U-M research units and its benefit to U-M data science research and/or to the larger community.  If your theme is selected, the symposium program committee will discuss with you further to help finalize the plan, and MIDAS will provide logistics support.

Some examples of possible themes: Mobilizing data science for crisis response; Data preparation for multi-party computing; Introduction of data science to attendees from non-profit organizations; Data science for wearables/mobile health.

If you would like to discuss your mini-workshop idea with the symposium committee before submission, please email Jing Liu, MIDAS Managing Director (ljing@umich.edu),

2. Abstracts for Research Talks (20 minutes including Q&A).  The talks should discuss exciting research ideas, provide vision and context for challenging data science questions, stimulate discussions, and lay out collaboration opportunities.  These talks should not simply be technical reports of projects.

3. Abstracts for Posters.  The Posters can be used as technical reports of projects.  Posters with students as first authors will be automatically entered in the poster competition.

DEADLINES:

Mini-workshop proposal submission: 11:59 pm, July 31, 2020; notification: Aug. 14, 2020
Talks and posters abstract submission: 11:59 pm, Sept. 18, 2020; notification: Oct. 9, 2020

SUBMISSION INSTRUCTIONS:

  • At least one author/presenter should have a U-M affiliation.
  • Please do not include figures, tables or bibliography in the abstract.
  • To submit proposals for mini-workshops:
    • Please include a title, list of organizers/potential presenters and their affiliations.
    • The main body of the submission should be no more than 300 words.
    • Please include the theme, format, how it features the strengths from multiple U-M research units, and its impact.
  • To submit abstracts for research talks and posters:
    • Please include a title, list of authors/presenters and their affiliations.
    • The main body of the submission should be no more than 300 words.
    • For research talks, please include a brief summary of the research idea and its context, potential methods and impact, and how it can benefit from collaboration.
    • For posters, please include a brief summary of the research, methods, main results and impact.

For questions, please contact midas-research@umich.edu.