WiDS logo (silhouette of woman with flowing hair filled in with binary code) and the text Women in Data Science Stanford @ Lane Medical Library. On the right, there is a 3x3 grid of photos of the event speakers.

Women in Data Science @ Lane Medical Library Virtual Conference

In celebration of International Women’s Day, Lane Library is announcing our 5th annual Women in Data Science (WiDS) Stanford @ Lane Medical Library regional event! Save the date for our half-day virtual conference on Wednesday, April 26th from 9AM to 12:30PM

WiDS Stanford @ Lane Medical Library is an independent event that is organized by Lane Medical Library as part of the annual WiDS Worldwide conference, the WiDS Datathon, and an estimated 200 WiDS Regional Events worldwide. Everyone is invited to attend all WiDS conference and WiDS Datathon Workshop events which feature outstanding women doing outstanding work.

WiDS @ Lane Medical Library aims to inspire, engage, and support data scientists and women in the field. The theme for Lane Library’s 2023 event is Connecting Health and the Environment through Data. We have an exciting line-up of speakers this year!

Register today to save the date! Registration is free and open to the Stanford Medicine community and beyond.

Agenda

9:00 AM – 9:10 AM
Welcome & Opening Remarks
Colleen Cuddy — Lane Medical Library

9:10 AM – 9:55 AM
Opening Keynote — The Accidental Data Librarian: A Journey to Data Science
Dr. Lisa Federer — National Library of Medicine

9:55 AM – 10:05 AM
Break

10:05 AM – 11:05 AM
“Connecting Health and the Environment through Data” Panelist Lightning Talks

  • Genomic Data Science for Planetary HealthDr. Julia Salzman, Biomedical Data Science, Biochemistry and Statistics (by Courtesy) @ Stanford University
  • Connecting the Dots from Bioengineering to Public Health to PathologyDr. Iny Jhun, Stanford Health Care
  • Exposure Uncertainty in Environmental Epidemiology: Statistical Approaches and OpportunitiesSaskia Comess, Interdisciplinary Environment and Resources Program @ Stanford University
  • Community Exposure Research in Bayview-Hunters PointDr. Ahimsa Porter Sumchai, Hunters Point Biomonitoring Foundation, Inc.
  • Precision Environmental Health Monitoring by Longitudinal Exposome and Multi-omics ProfilingDr. Xinyue “Allison” Zhang, Genetics @ Stanford University
  • Leveraging Data Science to Prevent Disease EmergenceDr. Caroline Glidden, Mordecai Lab @ Stanford University
  • The Interface of Vector Borne Disease and Community Empowerment: Creating a Healthier Community Through a Cleaner EnvironmentDr. Desiree LaBeaud, Pediatric Infectious Diseases @ Stanford Medicine

11:05 AM – 11:35 AM
“Connecting Health and the Environment through Data” Panel Q&A
Sam Wilairat — Lane Medical Library (Moderator)

11:35 AM – 11:40 AM
Break

11:40 AM – 12:10 PM
Closing Keynote — The Pipeline for Women in Data Science: Key Strategies with Social & Environmental Impact
Karen Matthys — Co-founder of WiDS and Executive Director of Stanford Medicine Biomedical Informatics Training Program

12:10 PM – 12:15 PM
Closing Remarks
Sam Wilairat — Lane Medical Library

3 comments on “Women in Data Science @ Lane Medical Library Virtual Conference”

  1. When I saw this conference, I immediately thought of Dr. Ahimsa Porter Sumchai who is biomonitoring the Bayview Hunter’s Point neighborhood. I don’t know if you have room for another speaker, but she would be a wonderful and important addition to this panel if she is available.

    https://alumni.ucsf.edu/stories/ahimsa-porter-sumchai
    https://www.kqed.org/science/1979614/for-these-black-bayview-hunters-point-residents-reparations-include-safeguarding-against-rising-toxic-contamination

    1. Hi Astrid,
      Thank you for the recommendation! I’ll reach out to the coordinator and let her know about your suggestion.
      Best,
      Katie

    2. Hello again, Astrid!
      I wanted to follow up and let you know that we were able to have Dr. Ahimsa Porter Sumchai join us for the panel (see the updated agenda).
      Thank you again for the recommendation!
      Best,
      Katie


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