Communications of the ACM
NSF Announces New Expeditions in Computing Awards
Two researchers at Harvard University work on a problem from a previously awarded Expeditions project. The three newly announced Expeditions bring the total number of projects currently receiving NSF support to ten.
Credit: Robert Wood / Harvard University
The Directorate for Computer and Information Science and Engineering (CISE) at the U.S. National Science Foundation (NSF) announced three new Expeditions in Computing awards Thursday (August 19). The awards will provide up to $10 million in funding over five years to each of the selected projects, representing the single largest investments made by the directorate in basic computer science research.
"There is a great deal of creativity in the computer science research community today," says Deborah Crawford, acting assistant director for CISE at NSF. "Our intentions with the Expeditions in Computing program are to stimulate and use that creativity to expand the horizons of computing," she says. "For example, several of the projects will be exploring new computational approaches to some of the most vexing problems we face in the science and engineering enterprise as well as in the larger society."
The Expeditions in Computing program made its debut in 2008 with four awards. With funding appropriated to NSF in 2009 through the American Recovery and Reinvestment Act (ARRA), the agency was able to support three trailblazer Expeditions. Today's announcement brings the total number of Expeditions projects currently receiving NSF support to ten. In the future, NSF will make Expeditions awards following an 18-month cycle.
Each award features a top-notch team working on one of the most challenging computing and information science and engineering issues today.
The three new Expeditions projects are:
Project: Computational Behavioral Science: Modeling, Analysis, and Visualization of Social and Communicative Behavior
Lead Principal Investigator: James Rehg, Georgia Tech
Collaborators: USC, Boston University, UIUC, CMU, MIT
It is well-known that the social and communicative behavior of children as young as 12-24 months contains important clues about their risk for a variety of developmental disorders, such as autism and Attention Deficit Hyperactivity Disorder (ADHD). Moreover, the ability to identify and treat such disorders at an early age has been shown to significantly improve outcomes. Autism represents a particularly compelling need in the US, since it affects one child in 110 with a lifetime cost of care at $3.2 million per person. This Expeditions project aims to develop novel techniques for measuring and analyzing the behavior exhibited by children and adults during face-to-face social interactions, including interactions between caregivers and children, children playing and socializing in a daycare environment, and clinicians interacting with children during individual therapy sessions. By developing methods to automatically collect fine-grained behavioral data, this project will enable large-scale objective screening and more effective therapy delivery and assessment to those in need, including socio-economically disadvantaged populations. More generally, this new computational technology will make it possible to automatically measure the behavior of large numbers of individuals in a wide range of settings over long periods of time. Other disciplines, such as education, marketing, and customer relations, could benefit from a more objective data-driven approach to behavioral assessment. The long-term goal of this project is the creation of a new scientific discipline of computational behavioral science, which draws equally from computer science and psychology in order to transform the study of human behavior.
Project: Understanding Climate Change: A Data Driven Approach
Lead Principal Investigator: Vipin Kumar, University of Minnesota
Collaborators: North Carolina A & T University, North Carolina State University, Northwestern University, University of Tennessee/Oak Ridge National Laboratory
Climate change is the defining environmental challenge facing our planet. Yet, there is considerable uncertainty regarding the social and environmental impact due to the limited capabilities of existing physics-based models of the Earth system. Consequently, important questions relating to food security, water resources, biodiversity, and other socio-economic issues over relevant temporal and spatial scales remain unresolved. A new and transformative approach is required to understand the potential impact of climate change. Data driven approaches that have been highly successful in other scientific disciplines hold significant potential for application in environmental sciences. This Expeditions project aims to address key challenges in the science of climate change by developing methods that take advantage of the wealth of climate and ecosystem data available from satellite and ground-based sensors, the observational record for atmospheric, oceanic, and terrestrial processes, and physics-based climate model simulations. These innovative approaches will help provide new understanding of the complex nature of the Earth system and the mechanisms contributing to the adverse consequences of climate change, such as increased frequency and intensity of hurricanes, precipitation regime shifts, and the propensity for extreme weather events that result in environmental disasters. Methodologies developed as part of this project will be used to gain actionable insights and to inform policymakers.
Project: Variability-Aware Software for Efficient Computing with Nanoscale Devices
Lead Principal Investigator: Rajesh Gupta, University of California, San Diego
Collaborators: Stanford, UC Irvine, UCLA, University of Illinois at Urbana-Champaign, University of Michigan
As semiconductor manufacturers build ever smaller circuits and chips, they become less reliable and more expensive to produce—no longer behaving like precisely chiseled machines with tight tolerances. Understanding the variability in their behavior from device-to-device and over their lifetimes—due to manufacturing, aging, and different operating environments—becomes increasingly critical. This project fundamentally rethinks the hardware-software interface and proposes a new class of computing machines that are not only adaptive but also highly energy efficient. It envisions a computing system where components—led by proactive software—routinely monitor, predict and adapt to the variability of the manufactured systems in which they are placed. These machines will be able to discover the nature and extent of variation in hardware, develop abstractions to capture these variations, and drive adaptations in the software stack from compilers to runtime to applications. The resulting computer systems will work while using components that vary in performance or grow less reliable over time and across technology generations. A fluid software-hardware interface will thus mitigate the variability of manufactured systems and make machines robust, reliable and responsive to the changing operating conditions. Changing the way software interacts with hardware offers the best hope for perpetuating the fundamental gains of the past 40 years in computing performance at a lower cost. In addition to plans for involving graduate and undergraduate students in the research, the team has built strong industrial ties and is committed to outreach to community high-school students through a combination of tutoring and summer school programs.
"Past Expeditions awards are beginning to show exciting results in a variety of applications and fields," says Mitra Basu, program director for the Expeditions program. "We're confident that this latest group of projects will continue to push the frontiers of computing."
No entries found