Early last Saturday morning, I had the privilege and pleasure of organizing and moderating a symposium at the American Association for the Advancement of Science’s (AAAS) 2012 Annual Meeting in Vancouver. The 90-minute session — titled Data to Knowledge to Action: Computational Science in a Global Knowledge Society — sought to describe how advances in computing research are enabling a “data to knowledge to action” pipeline that is increasingly critical for facilitating a 21st-century global knowledge society. Over 70 people packed into a small room in the Vancouver Convention Center to hear the session’s featured speakers, Eric Horvitz, Peter Stone, and Deborah Estrin (slide shows after the jump).

Eric led off the symposium by describing Hippocrates’ dream of evidence-based health care, and in particular, how he and his colleagues have been leveraging algorithms for machine learning and decision making, plus infrastructure for capture of electronic data, to generate new insights and efficiencies from the collection and analysis of large amounts of clinical data. In one example, he showed a predictive modeling approach that risk-stratifies readmission probability at the time of inpatient discharge, with the goal of reducing costly hospital readmissions.

Peter presented his group’s work on traffic intersection management — a novel multiagent intersection control mechanism in which autonomous driver agents “call ahead” and reserve space-time in the intersection, pending the approval of an arbiter agent called an “intersection manager” located at the intersection. This solution is a step toward intelligent transportation systems, which aim to use artificial intelligence to make transportation safer, cheaper, and more efficient.

And Deborah wrapped the session by describing participatory sensing systems leveraging mobile phones and the cloud to offer unprecedented observational capacity at the scale of the individual. These systems can be used by individuals and communities to address a range of personal, community, and environmental concerns, from safety to sustainability to chronic disease management and prevention. At the same time, Deborah described how they present a set of technical challenges in sense-making, usability, and data privacy.

The session drew interest from members of the media in the days leading up to it. For example, Peter’s work was picked up by Discovery News, PCWorld, Science Codex, and even Slashdot. According to the Discovery News write-up:

While scientists have been busy with making more accurate self-driving cars, at least one set of researchers has thought even further ahead and developed a smart intersection that can manage crossing flows of autonomous vehicles.

 

The intersections of the future will not rely on stoplights or stop signs. Instead, when cars are driven by software, they could be managed by virtual traffic controllers, which stay in close contact with the automobiles as they approach the intersection, said Peter Stone, a professor of computer science at The University of Texas at Austin.

 

On Saturday, Stone will present the latest of his team’s work on autonomous intersection management at the [AAAS] annual meeting this week in Vancouver, British Columbia.

Check out a video he featured in his talk below:

The AAAS symposium builds on a set of white papers the Computing Community Consortium (CCC) produced a year ago describing “Big Data” challenges in several areas of national priority, including healthcare and transportation, as well as energy, education, and national defense. And it’s quite timely, as there has been growing interest in recent months about this important area.

Many thanks to my colleagues for participating in Saturday’s session! You can view their slide shows (PDFs) here: Eric (12.9 MB), Peter (7.7 MB), and Deborah (4.1 MB).

(Contributed by Erwin Gianchandani, CCC Director)