Due to the COVID-19 epidemic, this event will be rescheduled to September, 2020.  More information coming soon.

MSU UM
Women+
Data Science

April 17, 2020
9:00 AM — 5:00 PM
Lake Huron Room, MSU Union

Michigan State University & University of Michigan invite you to their joint Women+ Data Science Symposium, 2020!
Transportation provided from Ann Arbor to East Lansing
EVENT REGISTRATION
Poster & Talk Guidelines

Poster & Talk Guidelines

Proposals are allowed for either:

  • Poster Presentation only,
  • 10 minute Talk only, or
  • 10-minute Talk with supporting poster

Be sure to select only one of these options when submitting.

REGISTER HERE

Submission instructions

  • Submit your abstract through the registration form.
  • Include a title, list of authors/presenters and their affiliations.
  • To recognize women and gender minority data scientists on your team, please indicate their roles in the project (securing research funding, project design, data collection, analysis and interpretation, writing, project management, project supervision).
  • We strongly encourage the women and gender minority members of your team to be the presenters of the talks or posters.
  • The main body of the abstract should be no more than 300 words and should include a brief summary of the research, methods, main results and impact.
  • Please do not include figures, tables or bibliography in the abstract.

Posters

Posters are a way for attendees to present early results, gain feedback from conference attendees, find collaborators on a topic, and/or spark discussion among conference participants. The intent is for these posters is similar to lightning talks in that they provide a venue in support of new ideas and newcomers to the Data Science community. The poster can be up to 36×48 inches / 91*122 cm.

NOTE: If work being submitted has been accepted for publication, please share the citation.

Talks

The talks are strictly-timed to 10-minute presentations intended to further expand the Data Science community and spark discussion among participants. The intent is for these talks to provide a venue in support of new ideas and newcomers to our community. Short Talks are a great way to get early feedback on a work in progress, to demo a new tool or technique, and to find potential collaborators at other units/institutions. Talk presenters may elect to present a poster in conjunction with their talk to provide additional information to curious parties and help foster post-talk discussion.

NOTE: If work being submitted has been accepted for publication, please share the citation.

Here are some short talk tips:

  1. Describe your problem and convince your audience right away as to why it’s important & what are the current gaps
  2. What is your cool approach?
  3. Demonstrate the effectiveness of your approach with one or two clear examples.
  4. Conclude with why your work matters!
  5. Preferably use more figures/flowcharts in place of full sentences and lots of text.

Submission Deadline for Posters and Talks

Submissions for consideration as short talks and posters should use the provided google form and are limited to a maximum of 300 words. Abstracts should be submitted no later than Feb 29th, midnight EST. Abstracts will be evaluated with respect to their relevance to the W+DS audience and on space availability in the conference program. Abstracts do not receive peer-review feedback. Accepted abstracts will be made available on the conference website prior to the event unless otherwise noted, but they will not be included in the conference proceedings.

Review Criteria

Talks and Posters submitted to W+DS should aim to do at least one of the following:

  • Solicit feedback from the community regarding a Data Science project (including sharing project plans and/or initial results)
  • Describe a new Data Science project for which the author(s) are seeking collaborators
  • Share encouraging initial results from a Data Science project
  • Demonstrate a new tool or technique

Contact

If you have any questions please contact us at women.plus.datascience@gmail.com.

Modified from: ICER, 2018; WiDS East Lansing @MSU, 2019

Organizers
R-Ladies East Lansing ,
Michigan Institute for Data Science
Camille Archer (RLEL, MSU), Janani Ravi (RLEL, MSU); Jing Liu (MIDAS, UM)


Program Committee
Liz Munch (MSU), Parisa Kordjamshidi (MSU), Dola Pathak (MSU)
Marcy Harris (UM), Margaret Hedstrom (UM).

Women+
Data Science

RLEL MIDAS MSU