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
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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.