Research
Featured Projects
AlignAlign: Software for Optimally Aligning Alignments
Sequence alignment is fundamental to unraveling the secrets of DNA. The AlignAlign software finds the optimal combination of two smaller alignments.
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ARRG: Arizona Robotics Research Group
The goal of the Arizona Robotics Research Group (ARRG) is to gain a greater understanding of learning and development in humans by creating artificial agents– both softbots and robots– that have to solve many of the same problems that the developing human brain has to solve. Many robots in the ARRG are essentially “baby robots”, which are created with minimal skill sets and uninterpreted sensors and go on to develop higher-level motor and perceptual skills from prolonged interaction with the world. Other robots are designed primarily to learn about human-robot interaction, particularly human-robot teaching. Central to most of this work is focused on the idea of “curiosity based learning” – that is, robots who’s primary drive is an intrinsic desire to better explain and control the world rather than the desire to maximize some external (human defined) reward.
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B2E2: Student Scientists
In collaboration with scientists at the UA Biosphere 2 and School of Natural Resources, we are developing information technology and methods to bring ongoing, cutting-edge science experiments into K-12 classrooms. The goal is to provide a direct conduit between scientists and the classroom to simultaneously enhance science education and enable experimental studies on a large scale. We have successfully run several variations of an evapotranspiration study in local schools and at the Biosphere 2; background information about the study was incorporated into the classroom science curriculum, and results from the experiments have directly informed the evapotranspiration study.
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Bootstrap Learning: The Bootstrapped Learning Project
The Bootstrapped Learning Project seeks to develop an electronic student capable of being taught new concepts through natural human instruction. There are many facets to the challenge of building an instructable student, and we are participating in a multi-team DARPA program focussed on this problem. We are developing algorithms to notice information and patterns that are not the explicit subject of the lesson being taught, both in teacher/student dialog and world events.
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FMDB: Flash Memory DBMS for Transactional Database Applications
Flash memory storage devices are now considered to have tremendous potential as a new storage medium that can replace magnetic disks. Flash memory, however, has its own limitations such as erase-before-update and exhibits poor performance for small-to-moderate sized writes requested in a random order.
The goal of this project is to develop new flash-aware designs and optimization strategies that allow large-scale transactional database applications to run efficiently on computing platforms equipped with flash memory storage devices as a main storage medium.
This project achieves its goal by (1) analyzing the performance implications of different I/O workloads on flash memory, and the applicability of flash memory to different types of tablespaces in databases, (2) inventing new paradigms, designs, data structures and algorithms, hot spot separation, and write optimization techniques, so that enterprise database servers can run on the target computing platforms efficiently.
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GMap: An Algorithm for Visualizing Graphs as Maps
GMap is an algorithm for visualizing graphs as maps. Information visualization can be invaluable in making sense out of large data sets. However, traditional graph visualization methods often fail to capture the underlying structural information, clustering, and neighborhoods. GMap, provides a way to overcome some of the shortcomings with the help of the geographic map metaphor. While graphs, charts, and tables often require considerable effort to comprehend, a map representation is more intuitive, as most people are very familiar with maps and even enjoy carefully examining maps. The effectiveness of GMap is illustrated with examples from several domains, namely TV shows, Amazon books, and last.fm music.
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Graphael: A System for Generalized Force-Directed Layouts
Graphael implements several classic force-directed layout methods, plus several novel non-Euclidean geometric approaches including hyperbolic and spherical. The system can handle large graphs, using multi-scale variations of the force-directed methods.
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GraphSet: A Simultaneous Embedding Tool
Problems in simultaneous graph drawing involve the layout of several graphs on a shared vertex set. This tool can be used for several types of these problems: simultaneous geometric embedding, simultaneous embedding with fixed edges, and colored simultaneous embedding. The tool can be used in two ways: (i) to study theoretical problems in simultaneous graph drawing; and (ii) to produce drawings from known algorithms for these problems.
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iPlant: Cyberinfrastructure for Plant Sciences
Several Computer Science faculty and students are involved in the iPlant Collaborative,
which is building a national cyberinfrastructure to enable the solution of "grand challenge" problems in the plant sciences. The national project is led by a University of Arizona team and is
funded by a $50 million grant from the National Science Foundation. Gregory Andrews is
on the leadership team for the project. He and John Hartman are supervising a research
project to build tools for reproducing software experiments.
Kobus Barnard is leading a project to evaluate the use of
educational video searching and browsing in the context of iPlant.
John Hartman and David Lowenthal are supervising a project to evaluate the use
of graphical processing units to speed the construction of evolutionary trees for the
iPlant tree-of-life grand challenge.
Suzanne Westbrook is leading efforts to develop materials for teaching computational
thinking to college students in the physical and life sciences.
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MathGap: Helping English-Language Learners Do Better in Math
This project studies the problem-solving strategies of students who are learning English, using word problems from the AnimalWatch online math tutoring system. The results will drive adaptations of the system to help ELLs improve their math skills.
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SOLAR: Software Optimization at Link-time And Run-time
Link-time binary rewriting offers optimization opportunities unavailable to compilers that process smaller code units. The SOLAR project is developing techniques for flexible link-time and run-time modification of application and system code.
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Stork: Scalable Software Management for Distributed Systems
Stork provides an intelligent, secure, and scalable way to manage software. In VM environments such as PlanetLab, software is securely shared to minimize disk, network, and memory costs. For scalability, Stork provides a simple way to manage software on a large number of nodes.
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τBerkeleyDB: Tamper Detection in Databases
Enron and WorldCom have shown that insiders, even official auditors, may tamper with corporate databases. Here's how to catch the bad guys.
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