What does the field of science look like? Is there a metaphor that can accurately describe millions of scientists in hundreds of countries, simultaneously collaborating, competing, and crawling towards new discoveries? In his talk at the Computation Institute on February 3rd, UCLA’s Jacob Foster proposed one humble comparison -- the complex communities of ants.


Around the world, cities are showing signs of old age. For urban areas, one of the first signs of advancing years comes in its circulatory system — the water infrastructure — as pipes laid underground over a century ago start to break down. Beyond the direct cost of repairing water main breaks and replacing the broken components, these incidents cause major headaches for nearby residences, businesses, and traffic. Last summer, Data Science for Social Good partnered with the City of Syracuse to help address this problem proactively by predicting where future water main breaks would occur. 


For the past four years, the Data Science for Social Good summer fellowship has brought over 160 fellows from around the world to Chicago to work on data-driven projects with real world significance. They've used machine learning and predictive analytics to improve graduation rates, anticipate urban blight and water infrastructure issues, direct hazardous waste inspections, deliver targeted social services, and much more. Now, the program, run by the CI's Center for Data Science and Public Policy, is looking for fellows, mentors, project managers, partners, and funders for 2017, with applications due at the end of January.


Urban Center for Computation and Data

The Urban Center for Computation and Data unites scientists from the University of Chicago and Argonne National Laboratory with educators, architects and government officials to capitalize upon the growing availability of city datasets and the emergence of urban sensor networks. The interdisciplinary collaboration will analyze and integrate those data sources and build complex computer models that can anticipate the impact of policy decisions, investments, urban development or other interventions on a city and its residents.

Knowledge Lab logo

Knowledge does not arise from the simple accumulation of facts. Rather, it is a complex, dynamic system, and its emergent outcomes - including scientific consensus - are unpredictable. The complexity of knowledge creation has exploded with the growing number of participating scientists and citizens. If human knowledge is to grow efficiently, we need a deeper understanding of the processes by which knowledge is conceived, validated, shared and reinforced. We need to understand the limits of knowledge in relation to these processes. In short, we need knowledge about knowledge.

The Eric & Wendy Schmidt Data Science for Social Good fellowship is a University of Chicago summer program for 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, transportation, and more. For three months in Chicago they apply their coding and analytics skills, collaborate in a fast-paced atmosphere, and learn from mentors coming from industry, academia, and the Obama campaign.

Researcher Spotlight