The following Great Innovative Idea is from Patrick Wiener from Karlsruhe University of Applied Sciences. Wiener along with his coauthors Manuel Stein and Daniel Seebacher from University of Konstanz, Julian Bruns, Matthias T. Frank, Viliam Simko, and Stefan Zander from FZI Research Center for Information Technology, and Jens Nimis from Karlsruhe University of Applied Sciences were among the winners at the Computing Community Consortium (CCC) sponsored Blue Sky Ideas Track Competition at the ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems 2016 (SIGSPATIAL 2016) in San Francisco, CA. Their winning paper is called BigGIS: A Continuous Refinement Approach to Master Heterogeneity and Uncertainty in Spatio-Temporal Big Data.   The Innovative Idea Geographic information systems (GIS) are important for […]

The following is a blog post by Computing Community Consortium (CCC) AI Task Force Co-Chair Gregory D. Hager, Mandell Bellmore Professor of Computer Science at The Johns Hopkins University and CCC Director Ann Drobnis. The past year has seen an incredible amount of ink spilled on a singular topic: what does the future of AI portend for the nation and the world? Will AI technologies enhance productivity and quality of life, or will it disrupt labor markets and accelerate growth in income disparity and wealth concentration? Will AI research be used for the common good, or will it be “bought up” by the private sector and exploited for commercial gain? Is this […]

The following Great Innovative Idea is from Abdeltawab Hendawi from the University of Virginia. Hendawi along with his coauthors John Stankovic from the University of Virginia, Mohamed Khalefa from the University of Alexandria in Egypt, and Harry Liu and Mohamed Ali from the University of Washington Tacoma were among the winners at the Computing Community Consortium (CCC) sponsored Blue Sky Ideas Track Competition at the ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems 2016 (SIGSPATIAL 2016) in San Francisco, CA for their paper A Vision for Micro and Macro Location Aware Services.  The Innovative Idea Conventional location-aware services customize search results based on users’ current location. Categories of these services include (1) service […]

The following blog post is by CCC Vice Chair and Executive Council member and University of Wisconsin-Madison Professor Mark D. Hill and co-author of the report. In June 2016, I blogged about the successful Architecture 2030 Visioning Workshop, organized by Luis Ceze of the University of Washington and Thomas Wenisch of the University of Michigan, and partially sponsored by the Computing Community Consortium (CCC) in conjunction with ISCA’16 in Seoul, South Korea. Recently CCC released the final report Arch2030: A Vision of Computer Architecture Research over the Next 15 Years with the endorsement of more forty research leaders in the field. Key findings are below. Progress on these is necessary to provide the cost-performance improvements that information technology creators and beneficiaries have come to depend […]

The Computing Community Consortium (CCC) is charged with catalyzing and empowering the U.S. computing research community to articulate and advance major research directions for the field. To do so, the CCC needs truly visionary leaders — people with great ideas, sound judgment, and the willingness to work hard to see things to completion. Please help the computing community by nominating such people for the Council. Established in 2006 through a cooperative agreement between the U.S. National Science Foundation (NSF) and the Computing Research Association (CRA) — representing over 220 North American academic departments, industrial research labs, and professional societies with computing research interests, the CCC provides a voice for the national computing […]

The Computing Community Consoritum (CCC) is co-sponsoring with the Association for the Advancement of Artificial Intelligence (AAAI) one of several symposia in the AAAI 2016 Fall Symposium series on November 17-19, 2016 in Arlington, Virginia.  The Symposium on Accelerating Science: A Grand Challenge for AI aims to bring together researchers in relevant areas of artificial intelligence (e.g., machine learning, causal inference, knowledge representation and inference, planning, decision making), high performance data and computing infrastructures and services, and selected application areas (e.g., life sciences, learning sciences, health sciences, social sciences, food energy and water nexus) to discuss progress on, and articulate a research agenda aimed at addressing, the AI grand challenge of accelerating science. Learn more and […]