Agent-based modeling can be used to simulate any number of complex scenarios, from the evacuation of a city after a natural disaster to the actions of the immune system after a gunshot wound. The Complex Adaptive Systems group at Argonne National Laboratory, led by CI Senior Fellow Chick Macal, is a leader in developing these models, including creating a simulation of the entire city of Chicago to test the spread of MRSA, ebola, and other diseases.
Given its expeditionary namesake, it's only appropriate that Beagle -- the University of Chicago's supercomputer for biomedical research -- works with data from all around the world. But a recent project may qualify as the farthest-traveling data yet, as the HPC resource was used in a new genomic study of populations living in the Himalayan mountain range.
It's been almost a year since Chameleon, the experimental cloud computing testbed co-run by the Computation Institute and Texas Advanced Computing Center, went into full production for research use. Already, 600 users and 150 projects have used the system to test new uses and technologies for cloud computing, from finding unknown exoplanets to preventing cyberattacks. Last week, HPCwire spoke to CI Senior Fellow Kate Keahey and other members of the Chameleon team, surveying its early successes and previewing the innovations still to come.
UrbanCCD Director and Computation Institute Senior Fellow Charlie Catlett was named one of 25 “Doers, Dreamers & Drivers” of 2016 by Government Technology. The honor celebrates his work creating partnerships between Argonne National Laboratory, University of Chicago, and the City of Chicago on innovative projects such as Array of Things, Plenario, and OpenGrid.
While Data Science for Social Good sorts through nearly 900 applications for their 2016 summer fellowship, their 2015 projects continue to attract interest. Last week, the Charlotte Observer profiled DSSG's collaboration with the Charlotte-Mecklenburg Police Department, using data on officers, arrests, dispatches, and other sources to help predict negative interactions between police officers and the public.
In two recent studies, CI Senior Fellows James Evans and Andrey Rzhetsky built a network of millions of papers to ask an important question: is scientific research living up to its potential? Their analysis, conducted with UCLA's Jacob Foster and CI Director Ian Foster, found that science increasingly explores more incremental and conservative questions, avoiding the
This month's announcement of a $3.1 million National Science Foundation for Array of Things inspired a wave of enthusiastic coverage about the urban sensing project. The plan to install 500 sensor nodes, collecting data on Chicago's environment, infrastructure, and activity, was touted as an important step towards creating a "smart city," boosting data-driven public policy and community engagement.
Today, a scientist's most desired citation may be from a publication not often thought of as prestigious: Wikipedia. While the open, user-curated encyclopedia may have occasional credibility issues, it remains the first source many people -- even scientists themselves -- consult when faced with an unfamiliar topic. As such, a Wikipedia reference may expose more people to a particular research finding than any citation from a scientific journal.
Scientific American looked at the Data Science for Social Good fellowship project that seeks to evaluate and improve police department early warning systems for predicting officer behavior and adverse incidents. Another DSSG project, using predictive analytics to fight lead poisoning, was also recently featured in the Chicago Tribune.