The following Great Innovative Idea is from Yonatan Bisk, Assistant Professor in the School of Computer Science and member of the Language Technologies Institute at Carnegie Mellon University. The Idea Language learning requires physically existing in the world (not being just a brain in a jar). A child doesn’t learn language from reading Wikipedia.  They build rich models of the world by seeing and doing.  They understand other humans as socially intelligent and cooperative agents with whom to speak and from whom to learn.  Yet, natural language “understanding” systems have focused on training in an impoverished disembodied text-only setting — trying to download as much text off the internet and […]

The following Great Innovative Idea is from Somali Chaterji, Assistant Professor in the Department of Agricultural and Biological Engineering at Purdue University where she leads the Innovatory for Cells and Neural Machines. The Idea The idea behind my work is that there is strength in numbers — a distributed computing system that needs to run a computationally heavy application on scarce resources can do so by pooling together many weak to moderate devices in a federated setting and with security guarantees. The secret sauce in my work is to do the right level of approximation at the right point in space (which device) and at the right point in time […]

The following Great Innovative Idea is from Hussein S. Al-Olimat from The Ohio Center of Excellence in Knowledge-Enabled Computing (Kno.e.sis) at the Wright State University. Dr. Al-Olimat along with his coauthors Valerie L. Shalin, Krishnaprasad Thirunarayan, and Joy Prakash Sain 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 2019 (SIGSPATIAL 2019) in Chicago, IL. Their winning paper is called Towards Geocoding Spatial Expressions. The Idea The web and social media contain a vast amount of unstructured text with spatial referents. Meaningfully interpreting these referents by geocoding and localizing them is critical to support a wide-range of spatially-aware computing systems, […]

The following great innovative idea is from Yiqun Xie, who is a Ph.D. candidate at the University of Minnesota.  Xie along with his advisor and former Computing Community Consortium (CCC) Council member McKnight Distinguished Professor Shashi Shekhar, Professor Richard Feiock of Florida State University and Professor Joseph Knight from the Department of Forestry Resources at the University of Minnesota, received a Blue Sky Idea Award at the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. They were honored for their paper, “Revolutionizing Tree Management via Innovative Spatial Techniques.” The Idea Unawareness of tree locations and their spatial relationships with urban infrastructures have disturbed our communities with increasing frequency, scale and severity. For example, Emerald Ash Borer […]

The following great innovative idea is from Konstantin Todorov from the University of Montpellier and a researcher at the LIRMM laboratory within the FADO group. Todorov was one of the Blue Sky Awards at ISWC 2019 for his paper called Datasets First! A Bottom-up Data Linking Paradigm.  The Idea Data linking is understood as the task of establishing typed links between entities across different knowledge graphs via the help of automatic link discovery systems. We argue that the current generic approach to develop data linking solutions has reached its limits and suggest that a paradigm shift in the way we look onto this task needs to take place. We propose to enable the development of data-centric approaches for bottom-up […]

The following great innovative idea is from Mayank Kejriwal and Pedro Szekely from the University of Southern California. Kejriwal and Szekely were one of the Blue Sky Award winners at ISWC 2019 for their paper called Co-LOD: Continuous Space Linked Open Data. The Idea The Web has always been thought of as a collection of discrete elements; for example, the number of people with articles on Wikipedia, the number of likes for a post on Facebook, and so on. The collection of open, interlinked datasets (Linked Open Data) that forms the backbone of the Semantic Web is also discrete.  However, modern deep learning and Artificial intelligence methods operate in continuous spaces or in the realm of real numbers. […]