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WiDS Stanford Conference 2017

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On February 3, 2017, 400+ attendees gathered at Stanford University and 80 locations worldwide for the 2nd annual Women in Data Science (WiDS) Conference.

Speakers

Margot Gerritsen

Executive Director

Lori Sherer

WiDS Worldwide Advisory Committee Chair, Partner, Bain & Company

Caitlin Smallwood

VP, Data Science & Engineering, Search & Assistant, Google

Diane Greene

Senior Vice President, Google

Miriah Meyer

Professor at University of Utah

Sinead Kaiya

COO at SAP

Janet George

CVP Data Center & Artificial Intelligence, GM Cloud Enterprise, AI, Security Solutions Group, Intel Corporation

Megan Price

Executive Director, HRDAG (Human Rights Data Analysis Group)

Fei-Fei Li

Associate Professor at Stanford University

Deborah Frincke

Associate Labs Director, National Security Programs, Sandia National Laboratories

Susan Holmes

Professor of Statistics, Stanford University

Stephanie Gottlieb-Zeh

President, Agileo Ventures

Finale Doshi-Velez

Gordon McKay Professor of Computer Science, Harvard University

Claudia Perlich

Data Scientist, Two Sigma

Videos

WiDS Stanford 2017 Highlights

TOPICS: Data Science as a Career , Values

WiDS 2017 Opening Video

TOPICS: Data Generation/Collection

Opening Remarks | Margot Gerritsen | WiDS 2017

TOPICS: Data Generation/Collection

A Quest for Visual Intelligence in Computers | Fei-Fei Li | WiDS 2017

TOPICS: Algorithms , Data Wrangling , Hardware

Margot Gerritsen, Director of Stanford ICME

TOPICS: Algorithms , Foundations (Mathematics/Statistics)

How Data Science is Revolutionizing the Oil & Gas Industry | Stephanie Gottlieb-Zeh | WiDS 2017

TOPICS: Algorithms , Data Generation/Collection , Foundations (Mathematics/Statistics) , Hardware , Values

Keynote Address | Diane Greene | WiDS 2017

TOPICS: Algorithms , Data Generation/Collection , Data Science as a Career , Hardware , Software Design and Engineering

Data Science Supporting National Security | Dr. Deborah Frincke | WiDS 2017

TOPICS: Algorithms , Data Generation/Collection , Data Wrangling , Values

Making a complete toolbox for quantitative biological data analyses | Susan Holmes | WiDS 2017

TOPICS: Data Generation/Collection , Data Wrangling , Foundations (Mathematics/Statistics) , Values

Designing Visualizations: A Systematic Approach | Miriah Meyer | WiDS 2017

TOPICS: Algorithms , Data Wrangling , Values

Fireside Chat | Lori Sherer & Caitlin Smallwood | WiDS 2017

TOPICS: Algorithms , Data Generation/Collection , Foundations (Mathematics/Statistics) , Values

Data Science, Making the World Run Better | Sinead Kaiya | WiDS 2017

TOPICS: Algorithms , Data Wrangling

Industrialized Data Science – Practical use cases | Janet George | WiDS 2017

TOPICS: Algorithms , Hardware

What Machine Learning Can Do for Healthcare | Finale Doshi-Velez | WiDS 2017

TOPICS: Algorithms , Data Wrangling , Foundations (Mathematics/Statistics)

Beware what you ask for: The secret life of predictive models | Claudia Perlich | WiDS 2017

TOPICS: Algorithms , Data Generation/Collection , Data Wrangling , Foundations (Mathematics/Statistics)

Machine Learning to Determine How Many People Have Been Killed in Syria | Megan Price | WiDS 2017

TOPICS: Foundations (Mathematics/Statistics) , Software Design and Engineering

Closing Remarks | Margot Gerritsen | WiDS 2017

TOPICS: Foundations (Mathematics/Statistics)

Other Media

Youtube Playlist