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NSF Press Release


NSF PR 03-103 - September 17, 2003

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 David Hart

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Program contact:

 Ty Znati

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Data Privacy, Emergency Response, Weather Prediction to Benefit from Information Technology Advances
NSF Information Technology Research program announces awards for 2003

ARLINGTON, Va.—Protecting individual privacy in a networked world, getting the right information at the right time for emergency response, predicting high-impact local weather such as thunderstorms, and monitoring wetlands with networks of mobile robotic sensors are the challenges being addressed by four of the eight large projects funded this year by the National Science Foundation (NSF) in the Information Technology Research (ITR) program.

The other four large ITR awards will design secure and reliable network architectures for bringing high-speed networking to millions of homes; create tools for comparing collections of DNA sequences and construct a "family tree" for life on Earth; harness automated microscopy and data mining of biological image databases to observe and understand cellular and molecular processes; and simplify the way scientists develop applications for grid computing.

"This year's ITR awards demonstrate how fundamental computer science research, combined with other research disciplines and practical activities, makes it possible to address new scientific questions and urgent national priorities," said Peter Freeman, head of NSF's Computer and Information Science and Engineering directorate.

Large ITR projects focus on long-term innovations through coordinated research and education efforts at the intersection of computer science and other science and engineering fields. This year's eight large ITR awards involve researchers from nearly 50 universities, companies, non-profit organizations and government agencies in 20 states and the District of Columbia. The eight projects were each awarded between $7.5 million and $12.5 million over five years.

This year, NSF awarded more than $169 million in new awards through the ITR program. In addition to the eight large projects, more than 175 mid-sized projects have been awarded up to $4 million for three to five years, and 180 smaller projects will each receive up to $500,000 for up to three years. The projects were selected by merit review from a landslide of more than 2,500 proposed projects from the academic community.

Notably, more than 800 proposals were related to homeland security, including proposals on analyst support, language processing, knowledge discovery and dissemination, biometrics, bioterrorism countermeasures, critical infrastructure protection, cybersecurity and other areas. As a result, NSF collaborated with other agencies, which are providing an additional $4.6 million to co-fund projects relevant to those agencies' missions.

"The academic community clearly has a wealth of innovative ideas for applying information technology to homeland security challenges," Freeman said. "We're pleased that the cutting-edge research supported by the ITR program will also enhance the country's capabilities in this critical area."

The ITR program encourages and stimulates innovative, high-risk and high-return multidisciplinary research that extends the frontiers of information technology, improves our understanding of its impacts on society, helps prepare Americans for the Information Age, and reduces the vulnerabilities of society to catastrophic events, natural and man-made. In addition to augmenting the nation's information technology knowledge base and strengthening the information technology workforce, the ITR program fosters visionary work that could lead to major advances, new and unanticipated technologies, revolutionary applications or new ways to perform important activities.

Further details on this year's eight large ITR awards are provided in the attached descriptions.


ITR program:

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Attachment: Large ITR Awards for 2003

Large ITR Awards for 2003

The following eight large ITR awards have been made for 2003. The funding levels for each award represent the estimated budget over a five-year period.

Sensitive Information in a Wired World
Project Director: Dan Boneh, Stanford University
Collaborators: Yale University, University of New Mexico, New York University, Stevens Institute of Technology, U.S. Secret Service, U.S. Census Bureau, Department of Health and Human Services, Microsoft, IBM, Hewlett Packard, Citigroup, Center for Democracy and Technology, Electronic Privacy Information Center
Amount: $12.5 million

The increased use of networked computers and databases in almost every aspect of daily life has led to a proliferation of sensitive data, but without a comprehensive infrastructure for handling these data over their lifetime. This project will develop methods for privacy-preserving data mining that respect and protect individual rights but allow law enforcement and legitimate users to mine massive data sets. The research team will also develop database tools that enforce privacy policies while managing sensitive data and release tools for end-users to prevent identity theft via spoofed or malicious Web sites.

Responding to the Unexpected
Project Director: Sharad Mehrotra, University of California, Irvine
Collaborators: University of California, San Diego; University of Maryland; Brigham Young University; University of Colorado; University of Illinois, Urbana-Champaign; ImageCat, Inc.
Amount: $12.5 million

This project aims to create robust information systems that enable first responders and decision-makers to make well-informed and better decisions, to prioritize their responses, and to focus on activities that have the highest potential to save lives and property. Such information systems must provide access to the right information by the right individuals and organizations at the right time. Social scientists play a crucial role in this project to investigate the nature of dynamic virtual organizations, such as the multi-agency response teams formed at the site of a disaster, and the social and cultural aspects of information sharing in such situations.

Predicting High-Impact Local Weather
Project Director: Kelvin Droegemeier, University of Oklahoma
Collaborators: Colorado State University; Millersville University; Indiana University; University of Alabama, Huntsville; Howard University; UCAR; University of Illinois, Urbana-Champaign
Amount: $11.25 million

Today's weather forecast models run on fixed schedules over fixed regions, independent of the type of weather that may be occurring. This project will develop grid-computing environments for on-demand detection, simulation and prediction of high-impact local weather, such as thunderstorms and lake-effect snows. With new tools for orchestrating complex flows of information, hazardous weather detection systems and forecast models will be able to reconfigure themselves in response to evolving weather and also guide the operation of observing systems such as Doppler radars to provide optimal input for the models. This project will hasten the transition of research results to operational use and bring the teaching benefits of sophisticated atmospheric science tools into high school classrooms for the first time. Ultimately, this project will help reduce the hundreds of lives lost and $13 billion of economic damage that hazardous weather causes each year in the United States.

Mobile Robotic Sensor Networks
Project Director: William Kaiser, UCLA
Collaborators: University of California, Riverside; University of Southern California
Amount: $7.5 million

This project will deploy a new class of aerial, suspended robotic sensors that can monitor their own sensing performance and move themselves along a light, easily deployed network of cable systems to make the most of their monitoring abilities. Test networks will explore and monitor a mountain stream ecosystem from the ground to the treetops for global change indicators and monitor coastal wetlands and urban rivers for biological pathogens. By configuring itself autonomously, the sensor network can select the best sensing tools and arrangements for each scientific task. The same technologies could one day be applied to securing and monitoring public infrastructure.

100 Megabits per second to 100 Million Households
Project Director: Hui Zhang, Carnegie Mellon University
Collaborators: University of California, Berkeley; Fraser Research, Inc.; Internet2; Rice University; Stanford University; Pittsburgh Supercomputing Center; AT&T Research Labs
Amount: $7.5 million

The growing demand for communications combined with newly emerging technologies have created a once-in-a-century opportunity to upgrade the country's network infrastructure, bringing 100 megabit-per-second Internet access to millions of homes in America within the next few years. Such a capability will have a dramatic effect on daily life, but only if the network is much more reliable, anticipates applications not yet envisioned, is economically sustainable for the long run, is easier to use and operate and is more secure than the Internet is today. The project will design blueprints for this near-future network by applying principles from security, economics and network research.

Constructing a "Family Tree" for Life on Earth
Project Director: Bernard Moret, University of New Mexico
Collaborators: University of California, San Diego; University of California, Berkeley; Florida State University; University of Texas, Austin; SUNY Buffalo; Yale University; University of Pennsylvania; University of Arizona; University of British Columbia; University of Connecticut; North Carolina State University; American Museum of Natural History
Amount: $11.6 million

By comparing DNA sequences, the genetic blueprints that determine the characteristics of every organism, scientists can predict the relationships of existing plants and animals to their common ancestors. The result is a "family tree" that describes which species has close common ancestors and which have more distant relations. Having this family tree for all living organisms would give biologists a better picture of how life has evolved on earth, a better understanding of where humans came from and a better interpretation of the forces underlying the diversification and adaptation of species. However, the diversity of life (at least 10 million species) is such that no currently available technique could reconstruct its family tree on even the largest supercomputers within our lifetime. This project will develop new analytical techniques, set up large repositories of evolutionary data and harness the power of many supercomputers to reconstruct this Tree of Life.

Data Mining for Biomolecular Imagery
Project Director: Bangalore Manjunath, University of California, Santa Barbara
Collaborators: Carnegie Mellon University; University of California, Berkeley; MIT
Amount: $9.4 million

This project will harness advances in molecular imaging to develop next-generation intelligent systems for observing and understanding the function, distribution and relationships of proteins and complex molecules in living cells. Capturing and organizing vast volumes of such biological images, to be housed in a distributed database, will require new information processing techniques in pattern recognition, data mining and databases. The end result will lead to a more complete and integrated understanding of cellular structure, function and regulation.

Simplifying the Development of Grid Applications
Project Director: Ken Kennedy, Rice University
Collaborators: University of California, Santa Barbara; University of California, San Diego; University of Houston; University of Illinois, Urbana-Champaign; University of Southern California Information Sciences Institute; University of Tennessee, Knoxville
Amount: $8.25 million

While grid computing promises to help solve problems in science and other fields by connecting computers, databases and people, the current difficulty of writing efficient programs to take advantage of such diverse resources limits its use. This project will create software tools to simplify and accelerate the development of grid applications and services. It will also look at novel scheduling techniques based on abstract "virtual grids" to deliver high efficiency on grids of real machines. Improved usability and efficiency should greatly expand the community of grid users and developers.




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