The inaugural Data Science for Social Good Conference took place in Chicago on August 24-25, 2016.

This conference highlighted the successes, opportunities, and challenges faced by the growing Data Science for Social Good community by bringing key members from each community (academia, governments, non-profits, foundations, social enterprises, and corporations) together to share best practices, learn from each other, and generate new collaboration opportunities.

If you weren’t able to join us at the conference, check out the descriptions and videos of the sessions below, and watch the video from the live stream of our final DataFest event, featuring presentations from the summer 2016 Data Science for Social Good fellows and a fireside chat with U.S. Chief Data Scientist DJ Patil.

If you attended the conference, we want to hear from you! Please fill out this survey and give us your feedback.

Trainings & Workshops

Data Science Project Scoping

Lauren Haynes & Joe Walsh

Data Maturity Framework  

Benedict Kuester & Jane Zanzig

Lightning Talks

 DSSG Programs Around the Country 

Session Chair: Benedict Kuester

University of Washington DSSG Program
Overview of DSSG at U of Washington
Sarah Stone

Challenges of Doing Data Science
in a University Environment
Ariel Rokem

CrowdSensing the Census
Rachael Dottle & Carlos Espino Garcia

Early Identification of Unsafe Food Products
Kiren Verma

Using Electronic Fare Card Transactions Data
to Improve Public Transit Equity

Sean Wang & Alicia Shen 

Global Open Sidewalks
Jess Hamilton & Tom Disley

GeorgiaTech DSSG Program
Xiang Chen (Emory University)

IBM DSSG Program
Hunting Zika Virus Using Machine Learning
Subho Majumdar (University of Minnesota Twin
Cities & IBM Research)

Data Science for Health & Safety 

Session Chair: Youngsoo Park

Machine Learning in Medicine
Ben Brew (Hospital for Sick Children)

The Power of Medicaid Data
Joe Orsini (Nuna Health)

Mining Web Data for Public Health
Mark Dredze (Bloomberg LP)

Using Data Commons to Share Genomic Data
for the Social Good
Robert L. Grossman (University of Chicago)

Difficulties in Predicting Police Misconduct
Kenny Joseph (Northeastern University)

Data Driven Policy Analysis Peace & Security
Amir Imani (Columbia University)


 What Does It Mean to do Social Good?

Matt Gee (Center for Data Science and Public Policy)

Elena Eneva (Accenture)

Adria Finch (City of Syracuse)

Bill Howe (University of Washington)

 Cities & Universities Partnering to Tackle Urban Challenges 

Ben Levine (Metrolab)

Santiago Garces (CIO of South Bend)

Lauren Haynes (University of Chicago)

Tom Schenk (CDO of Chicago)

Discussion Sections

Challenges in Data Maturity (Collection & Data Management for NPOs)

Facilitators: Young Jin Kim (Emphanos) & Joe Walsh (Center for Data Science and Public Policy)

Ethical Issues in Data Science for Social Good

Facilitators: Bill Howe (University of Washington) & Rob Mitchum (Data Science for Social Good)

Building Data Science Teams that Get Results

Facilitators: Emily Wiegand (Chapin Hall) & Paul van der Boor (Data Science for Social Good)

Replicability & Use Cases

Facilitators: Jane Wiseman (Harvard University) & Chad Kenney (Data Science for Social Good)

Managing Stakeholder & Team Relationships

Facilitators: Nick Bolten (University of Washington) & Lauren Haynes (Center for Data Science and Public Policy)

Institutionalizing What You Build

Facilitator: Matt Gee (Center for Data Science and Public Policy)