UNM Computer Science

Grant Awards for 2007

New Grants at the Computer Science Department

The UNM Computer Science Department has received nine new grants in the past year. Projects include:

• Helix: A Self-Regenerative Architecture for the Incorruptible Enterprise
  Dept. Chair Stephanie Forrest and Prof. Saia will study self-regenerative enterprise systems, which are automated and proactive, and can adapt, reconfigure, and repair themselves. Funding comes from a five-year, million dollar grant from the Air Force Office of Scientific Research and the Multidisciplinary Research Program of the University Research Initiative (MURI). They will collaborate with investigators at the University of Virginia; University of California, Davis and University of California, Santa Barbara.
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• RI: Synergistic Machine Learning: Collaboration and Topology Exploitation in Dynamic Environments
  This NSF grant, in which Prof. Lane is collaborating with Kiri Wagstaff of JPL, focuses on using topology-aware machine learning methods on live sensor networks currently installed at Kilauea and Mt. Erebus, two active volcanoes.
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• Computational Methods for Understanding Social Interactions in Animal Populations
  This NSF grant allows Prof. Saia, Daniel Rubenstein and Tanya Berger-Wolf to focus on creating a powerful and general abstract mathematical model to capture the distinct properties of dynamic social networks, taking advantage of recent breakthroughs in data collection technology in the biological fields.
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• Modeling Early Influenza Virus Replication in Primary Human Lung Cells
  Fred Koster and Prof. Forrest received a grant from the NIH to study influenza replication in humans, both the H3N2 strains and H5N1 avian influenza strains, using an agent-based computer model and a complementary in vitro model.
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• CRI:CRD Libraries and Software for Automated Deduction
  Prof. Veroff has not let being an emeritus professor slow him down—he and William McCune have an NSF grant to work on easily accessible, documented software programs and libraries for high-performance first-order deduction.
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• Four-dimensional IMAT Planning Using Graph Algorithms
  A new cancer treatment, intensity-modulated arc therapy (IMAT), requires a practical planning method to deliver superior dose conformity with minimized treatment time. This National Cancer Institute Grant pairs Prof. Luan with Cedric X. Yu of the Department of Radiation Oncology, University of Maryland.
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• CCF-CPA: Visualization with Uncertainty
  Using an NSF grant, Prof. Kniss will develop visualization methods that make the concept of uncertainty a central component by concretely realizing ambiguous features, thereby allowing users to assess uncertainty even with noisy data sources.
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• Foundations for Attack-Resistant, Collaborative Peer-to-peer Systems
  This research aims to create algorithms to enable a group of hundreds of millions of people—a group the size of the entire population of the U.S.—to accomplish a collaborative task even if up to a one-third fraction of the group members are completely untrustworthy.  Prof. Saia received a a prestigious National Science Foundation CAREER Award for this research.
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