Events WiDS Stanford Conference 2019
WiDS Stanford Conference 2019
Summary
The WiDS 2019 Conference at Stanford University featured keynotes, technical vision talks, a career panel, lunchtime breakouts, and multiple opportunities to network with other attendees.
Event Type
Central Conference
Date
March 4, 2019
Time
8:00 am - 7:00 pm (UTC -8)
Location
Frances C. Arrillaga Alumni Center
326 Galvez Street
Event Type
Hybrid
Language
English
Sponsors
Walmart Labs
SAP
Microsoft
Google
Western Digital
Wells Fargo
Total
Amazon Web Services
IBM
Facebook
Stanford President's Office
Stanford Computer Forum
Social Links
Instagram
Facebook
Twitter
LinkedIn
Youtube
Event Program
March 4, 2019
12:15 - 1:45 PM
Lunch and Breakout Sessions -On livestream: WiDS interviews by theCube
3:30 - 4:10 PM
Career Panel
Natalie Evans Harris
Marzyeh Ghassemi
Emily Glassberg-Sands
Yinglian Xie
*All times are UTC -8
Speakers
Former Co-Director, WiDS Worldwide
Executive Director External Partners, Stanford University, ICME
Professor, Stanford University
President and CEO at Fable
Chief Technology Officer, Indyx
Healthy Machine Learning @
MIT EECS/IMES & Vector Institute
Chief Technical Advisor to the Associate Provost
UC Berkeley Computing, Data Science, & Society
Professor of Computing and Mathematical Sciences at CalTech and Director of Research in Machine Learning, NVIDIA.,
Founder & Executive Director, The Distributed AI Research Institute (DAIR)
Gordon McKay Professor of Computer Science, Harvard University
Vice President, Google Health
WiDS Worldwide Advisory Committee Chair, Partner, Bain & Company
CEO and Co-Founder, DataVisor, Inc.
Scientist / Engineer, Lawrence Livermore National Laboratory
Senior Advisor for Delivery (Tech and Data), Secretary of Commerce
Head of Information, Stripe
Associate Professor, Computer Science Department, Stanford University
Assistant Professor, Cornell
Videos
Alicia Carriquiry | Machine Learning and the Evaluation of Criminal Evidence | Stanford 2019
TOPICS:
Algorithms , Foundations (Mathematics/Statistics)
Better Reinforcement Learning for Human in the Loop Systems | Emma Brunskill | WiDS 2019
TOPICS:
Algorithms , Data Generation/Collection , Data Science as a Career , Data Wrangling , Foundations (Mathematics/Statistics)
Building Trust in the Digital Age | Yinglian Xie | WiDS 2019
TOPICS:
Algorithms , Data Wrangling , Foundations (Mathematics/Statistics)
Career Panel | WiDS 2019
TOPICS:
Algorithms , Data Generation/Collection , Data Science as a Career , Values
Closing Remarks | Margot Gerritsen | WiDS 2019
Differential Privacy and the US Census | Cynthia Dwork | WiDS 2019
TOPICS:
Algorithms , Foundations (Mathematics/Statistics)
Emily Glassberg-Sands | Data Science for Unlocking Teaching & Learning at Scale | WiDS Stanford 2019
TOPICS:
Algorithms , Data Generation/Collection , Data Science as a Career , Foundations (Mathematics/Statistics) , Software Design and Engineering , Values
Evolution of Machine Learning for NIF Optics Inspection | Laura Kegelmeyer | WiDS 2019
Filling in Missing Data with Low Rank Models | Madeleine Udell | WiDS 2019
TOPICS:
Algorithms , Data Science as a Career , Data Wrangling , Values
Fireside Chat | Yoky Matsuoka & Lori Sherer | WiDS 2019
TOPICS:
Algorithms , Data Generation/Collection , Data Science as a Career , Values
Improving Health Requires Targeting and Evidence | Marzyeh Ghassemi | WiDS 2019
TOPICS:
Algorithms , Foundations (Mathematics/Statistics) , Values
Infusing Structure into Machine Learning Algorithms | Anima Anandkumar | WiDS 2019
TOPICS:
Algorithms , Foundations (Mathematics/Statistics) , Software Design and Engineering , Values
Janet George, Western Digital | WiDS 2019
TOPICS:
Algorithms , Data Generation/Collection , Data Science as a Career , Data Wrangling , Software Design and Engineering , Values
Kavita Sangwan, Intuit | WiDS 2019
TOPICS:
Algorithms , Data Science as a Career , Values
Kristina Draper, Wells Fargo | WiDS 2019
TOPICS:
Algorithms , Data Generation/Collection , Data Science as a Career , Data Wrangling , Values
Liza Donnelly, The New Yorker | WiDS 2019
TOPICS:
Data Generation/Collection , Data Wrangling
Machine Learning and the Evaluation of Criminal Evidence | Alicia Carriquiry | WiDS 2019
TOPICS:
Algorithms , Foundations (Mathematics/Statistics)
Natalie Evans Harris, BrightHive | WiDS 2019
TOPICS:
Algorithms , Data Science as a Career , Values
Opening Address | Jennifer Widom | WiDS 2019
TOPICS:
Data Generation/Collection , Data Science as a Career , Data Wrangling
Srujana Kaddevarmuth, Accenture | WiDS 2019
TOPICS:
Algorithms , Data Generation/Collection , Data Science as a Career , Foundations (Mathematics/Statistics)
Technology Driven Business Opportunities for the Next Decade | Padmasree Warrior | WiDS 2019
TOPICS:
Algorithms , Data Generation/Collection , Data Science as a Career
Using Data Effectively: Beyond Art and Science | Hilary Parker | WiDS 2019
TOPICS:
Algorithms , Foundations (Mathematics/Statistics)
Timnit Gebru | Understanding the Limitations of AI | WiDS Stanford 2019
TOPICS:
Algorithms , Data Science as a Career , Software Design and Engineering , Values
Understanding the Limitations of AI: When Algorithms Fail | Timnit Gebru | WiDS 2019
TOPICS:
Algorithms , Data Science as a Career , Values
WiDS Datathon Winners Announced | Meredith Lee | WiDS 2019
TOPICS:
Algorithms , Data Generation/Collection , Data Wrangling
