Events | WiDS Stanford Conference 2023
WiDS Stanford Conference 2023
Summary
On March 8, 2023, thousands of participants gathered around the globe for the Women in Data Science (WiDS) Stanford Conference.
View the conference program and watch conference videos from WiDS Worldwide on YouTube!
Event Type
Central Conference
Date
March 8, 2023
Time
8:30 am - 4:30 pm (UTC -8)
Location
Frances C. Arrillaga Alumni Center
326 Galvez Street
Event Type
In-Person
Language
English
Sponsors
Walmart Global Tech
Wells Fargo
TotalEnergies
Gilead
Boeing
Intuit
MathWorks
Google
GM
Microsoft
Systematica Investments
Pinterest
Meta
Dataiku
Two Sigma
ICME
Stanford Data Science
Social Links
Instagram
Facebook
Twitter
LinkedIn
Youtube
Event Program
March 8, 2023
8:00AM - 8:30AM
Registration and Breakfast
10:50AM-10:55AM
Interlude: Announcing the WiDS Datathon 2023 Winners
4:30PM-6:00PM
Networking Reception & Career Expo
*All times are UTC -8
Speakers
Centre Manager, QUT Centre for Data Science
Professor of Communication and FSI Senior Fellow, Stanford University
Geophysicist-Data Scientist, Springboard Alumni
Staff Business Data Analyst, Intuit
Principal Cloud Advocate, Microsoft
Vice President of Data Science at Facebook
Chief Health Equity Officer at Merative & Affiliate Professor, GWU Milken Institute School of Public Health
Co-Founder and CEO, Krikey
Technologist, Computational Linguist, and Game Designer
Bioinformatics Group Leader, Lawrence Livermore National Lab
Executive Director, HRDAG (Human Rights Data Analysis Group)
ACM Distinguished Scientist, University of Tennessee Knoxville (UTK)
Assistant Professor at Rice University Electrical & Computer Engineering
Doctoral Student, University of Arizona
Co-Founder & Executive Director, Climate Change AI (CCAI)
Director of Master's Program, Education Data Science, Stanford University
Data Director, Invisible Institute
Computer Vision Tech Lead, Senior Data Scientist, Getty Images
Videos
Closing Remarks | Susan Malaika | WiDS Stanford 2023
TOPICS:
Data Science as a Career
Closing Activity | Jhanvi Shriram & Ketaki Shriam | WiDS Stanford 2023
TOPICS:
Data Science as a Career
Farewell | Margot Gerritsen | WiDS Stanford 2023
TOPICS:
Data Science as a Career
Gabriela de Queiroz, Microsoft | WiDS 2023
TOPICS:
Algorithms , Data Generation/Collection , Foundations (Mathematics/Statistics)
Gayatree Ganu, Meta | WiDS 2023
TOPICS:
Algorithms , Data Generation/Collection , Data Wrangling
Irene Dankwa-Mullan, Marti Health | WiDS 2023
TOPICS:
Algorithms , Data Generation/Collection , Data Science as a Career , Data Wrangling , Values
Jacqueline Kuo, Dataiku | WiDS 2023
Kelly Hoang, Gilead | WiDS 2023
TOPICS:
Algorithms , Foundations (Mathematics/Statistics) , Values
Keynote Analysis | WiDS 2023
TOPICS:
Data Generation/Collection , Foundations (Mathematics/Statistics)
Myriam Fayad & Alexandre Lapene, TotalEnergies | WiDS 2023
TOPICS:
Data Science as a Career , Values
Opening Address | Srinija Srinivasan | WiDS Stanford 2023
TOPICS:
Data Generation/Collection , Data Science as a Career , Values
Rhonda Crate, Boeing | WiDS 2023
TOPICS:
Data Science as a Career , Foundations (Mathematics/Statistics)
Shir Meir Lador, Intuit | WiDS 2023
TOPICS:
Algorithms , Values
WiDS 2023 Opening Video
TOPICS:
Algorithms , Data Science as a Career
WiDS Welcome | Margot Gerritsen | WiDS Stanford 2023
TOPICS:
Data Generation/Collection
Women in Data Science | Stories of Women from Around the Globe | WiDS Stanford 2023
TOPICS:
Data Generation/Collection , Featured , Values
theCUBE Insights | WiDS 2023
TOPICS:
Algorithms , Data Generation/Collection , Data Wrangling
Optimization in the loop machine learning for energy and climate | Priya Donti
TOPICS:
Algorithms , Data Generation/Collection , Foundations (Mathematics/Statistics)
Making Biosignal Interfaces Accessible | Momona Yamagami
TOPICS:
Algorithms , Data Wrangling , Foundations (Mathematics/Statistics)
Data Democratization Panel | Priya Donti, Julia Stewart Lowndes, Nikki Tulley, Michela Taufer
TOPICS:
Algorithms , Data Generation/Collection , Data Science as a Career , Foundations (Mathematics/Statistics) , Values