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Nova SBE, Municipality of Cascais and the University of Chicago are promoting a public panel session: “Using Data for Social Good and Public Policy: Examples, Opportunities, and Challenges”, next June 8, at 6:30pm, in the auditorium of Centro Cultural de Cascais.

This event is the launch for the project Data Science for Social Good: a challenge that the Nova SBE has launched to several public and private institutions in the area of health, municipalities and utility companies. These institutions are going to participate in this project for three months and will gather 25 data analytics experts from several countries who will be working using this data processing capability to try to find clues to solve relevant problems with impact on society.

During the public panel session next 8 of June, some questions are going to be discussed: How did the Obama White House work with police departments to tackle police violence and misconduct using data? How did the city of Chicago and Cincinnati use data to better target limited resources to improve lives of citizens? How does an NGO use data to estimate the size of a temporary refugee camp in war zones to organize the provision of help? How to successfully develop and maintain systems that use data to produce social good and inform public policy?

The experts from Portugal and abroad will discuss practical cases of using data to create social good and drive public policy. In this public panel, the experts will discuss how to develop human capital and inspire the new generation of data scientists to tackle high-impact public policy and social challenges in criminal justice, public health, education, economic development, public safety, workforce training, and urban infrastructure.

The opportunities and challenges around deploying and maintaining the data-driven systems as new data comes in, and in dealing with issues of interpretability, bias, fairness, and transparency are other themes under debate.

About speakers:


Rayid Ghani

Director of the Center for Data Science and Public Policy, Research Director and Senior Fellow at the Computation Institute and a Senior Fellow at the Harris School of Public Policy at the University of Chicago. He was Chief (Data) Scientist at Obama for America 2012 campaign focusing on analytics, technology, and data. As Senior Research Scientist and Director of Analytics research at Accenture Labs, Rayid led a technology research team focused on applied R&D in analytics, machine learning, and data mining for large-scale & emerging business problems in various industries including healthcare, retail & CPG, manufacturing, intelligence, and financial services. Rayid holds MSc from Carnegie Mellon University.

Euro Beinat

Professor at the University of Salzburg (Austria), and the Chairman of CS Research (Netherlands). He was the Advisor to the Italian Minister of Cultural Heritage and Tourism on digital strategies, Vice President of Zebra Technologies Corporation, CEO of Geodan Mobile Solutions, Chairman of Currentcity, and the director of the Spatial Information Laboratory of the Free University in Amsterdam. Euro holds a PhD in Economics from Tinbergen Institute.

Mirsad Hadzikadic

Professor of Software and Information Systems in the College of Computing and Informatics at The University of North Carolina at Charlotte. He is also the Founding Executive Director of the Data Science Initiative at UNCC and Director of the Complex Adaptive Systems Institute. He holds a Ph.D. in Computer Science from Southern Methodist University and a Master in Public Administration from the Harvard Kennedy School of Government.

About Data Science for Social Good:

The Data Science for Social Good Fellowship is a summer program to train aspiring data scientists to work on data mining, machine learning, big data, and data science projects with social impact. Working closely with governments and nonprofits, fellows take on real-world problems in education, health, energy, public safety, transportation, economic development, international development, and more.

Register here

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