Event
David Krakauer, Santa Fe Institute
October 06, 2017
Searle 240

Computational Social Science and Public Policy Colloquium & Data Lunch Seminar
 
Speaker: 
David Krakauer, President, Santa Fe Institute

Press Release

For the future of the planet, there are few research subjects more important than the global supplies of food, water, and energy. To comprehensively study, understand, and inform policy around these complex systems, the next generation of researchers in the physical, social, and biological sciences will need fluency with data analysis methods that traverse traditional academic boundaries.

Event
Brendan Nyhan, Dartmouth College
June 09, 2017
Harris School Rm. 142

Brendan Nyhan (Dartmouth College) will give a talk for the Computational Social Science and Public Policy Colloquium.

Event
Susan Murphy, University of Michigan
May 05, 2017
Searle 240, 5735 S. Ellis Ave.

Abstract: A critical question in the development of mobile health interventions is, when and in which contexts, is it most useful to deliver treatments to the user.  This question

In The News
Politico

Politico Magazine features the Data Science for Social Good project with the City of Syracuse using data to predict water main breaks  so that the city can make proactive repairs rather than responding to catastrophe.

Event
Cynthia Rudin, Duke
April 14, 2017
Searle 240

Recent Work on Interpretable Machine Learning

Event
Jacob Foster, UCLA
February 03, 2017
Searle 240

Made to Know: Science as the Social Production of Collective Intelligence
Speaker: Jacob Foster, UCLA

Event
January 12, 2017
Searle 240, 5735 S. Ellis Ave.

The Center for Data Science and Public Policy has started a Data Science Happy Hour to get people across campus together who’re working in different areas us

Event
Tina Eliassi-Rad, Northeastern University
January 06, 2017
Harris School Rm. 142

The Reasonable Effectiveness of Roles in Complex Networks

In The News
Chicago Tribune

For the last two summers, fellows at Data Science for Social Good and researchers at the Center for Data Science and Public Policy (DSaPP) have worked with police departments around the country on developing a data-driven model for predicting police officer behavior.