SUMMIT: Final presentations of the Summer Fellowship Program of Data Science for Social Good Europe

by Nova SBE on .

22Brunch ● August 24th 2017 ● 10:30 a.m. ● Casa das Histórias Paula Rego, Cascais

Nova School of Business and Economics, the Municipality of Cascais and the University of Chicago, are inviting you to attend the Summit of the Summer Fellowship Program of Data Science for Social Good Europe, which will take place on August 24th, at 10:30 a.m. at the Casa das Histórias Paula Rego, in Cascais.

 

Data Science for Social Good is University of Chicago’s summer program, and this year it came to Europe – to Nova School of Business and Economics.

For three months, 18 brilliant minds developed data science solutions to problems with high social impact by analyzing big data.For three months, 18 brilliant minds developed data science solutions to problems with high social impact by analyzing big data.They worked in collaboration with national and international governments as well as non-profit organizations, facing challenges related to unemployment, health, energy, transportation, and economic and environmental development sectors.

The Summit will be a celebration of the 1st European edition of Data Science for Social Good summer Fellowship, and the Fellows will present the 6 projects they have been working on for the past three months.

PROJECT #1: Recommender systems for tackling (long-term) unemployment

Unemployment is a global problem, yet resources available to help affected individuals re-enter the labor market are scarce. Together with the Municipality of Cascais, Data Science for Social Good Europe Fellows are using data science to help understand who is at a higher risk of becoming long-term unemployed. Using this information resources can be provided early to people at high risk, increasing their chances of avoiding long-term unemployment.

PROJECT #2: Matchmaking between patients and doctors in a large healthcare network

Finding the right physician is hard. Wouldn’t it be nice if each patient could be matched with their ideal doctor? José de Mello Saude understands the importance of a stable patient-doctor relationship. Together with Data Science for Social Good Europe Fellows, they are looking into the relationships between doctors and patients. Their goal is simple: by optimizing the process of doctor-patient matchmaking, there is a higher likelihood of a long-lasting relationship and better health care.

PROJECT #3: Sustainable Tourism in Tuscany

Travelling has never been easier, cheaper, and faster. Tourism supports local economies and gives travellers new experiences. Tuscany is one of the worlds most coveted tourism destinations, and the large inflow of visitors greatly impacts the local economic and daily life, for good and bad. With the help of Data Science for Social Good Europe, different data sources were combined such as call data records and museum card data to understand where tourists go, what services they consume, and how long and where do they stay. Creating a more detailed picture of tourism in Tuscany allows a more data-driven approach to policy making, which should be more effective at maintaining the quality of life for both locals and tourists in Tuscany.

PROJECT #4: Improving incident response in the Netherlands

Road incidents, when not responded to on time can lead to serious consequences, including loss of life and traffic jams. But what if there was a way of knowing where and when incidents would happen? And what could be done with that information? Rijkswaterstaat operates a 24-hour service, dispatching road inspectors to respond to incidents. Data Science for Social Good Europe, together with the Ministry of Infrastructure and Environment in the Netherlands, uses data science to test how to allocate sufficient numbers of inspectors near high-risk locations, to minimize incident response time.

PROJECT #5: Developing a Fishing Risk Framework from Satellites and Ocean Data

The oceans are not only beautiful, but millions of people also depend on them for their food supply. As a result of high consumption of fish, illegal and overfishing activities are currently devastating the oceans at a rapid pace. The World Economic Forum, Spire, Digital Globe and Planet Labs have teamed up with Data Science for Social Good Europe to test new approaches to identify boats with high probability of fishing illegally. The team is combining satellite images with large ocean datasets and state of the art machine learning techniques in a way never done before, with the goal of reducing illegal fishing.

PROJECT #6: Identifying rooftop usage in Rotterdam

Rooftops: they provide shelter. But can they be more than just shelter? What if they could be used to make cities more sustainable and enjoyable?Rooftops: they provide shelter. But can they be more than just shelter? What if they could be used to make cities more sustainable and enjoyable?The Municipality of Rotterdam wants to maximize the potential of its 14 square kilometres of flat rooftop space for its citizens. Using data science, Data Science for Social Good Europe and the Municipality are working to identify rooftops and classify them according to their potential use. A roof with a green garden? A roof with solar panels? Imagine the possibilities!

TOGETHER WE ARE MAKING THIS HAPPEN