Research Awards

Some unknown physical and chemical phenomena can be precisely observed and engineered by manipulating fluids in micro and nano scales. PI?s long-term research agenda lies in the development of Integrated Microsystems to enable such interface and reverse-engineering on non-electric ambient phenomena by utilizing precision electro-mechanical transduction via fluidic movement. This 5-year CAREER proposal focuses on developing a ?wearable? micro gas chromatography (ìGC) system to enable real-time, on-spot, and personal monitoring of a class of various airborne pollutants (Volatile Organic Compounds: VOCs) for early warning for individuals. Specifically, PI proposes to investigate fundamental sciences of an entirely novel gas chromatography configuration that is expected to overcome the major barrier in miniaturization and enable the ultra-high capacity, selectivity, and portability beyond the current state-of-the-art technology.

To overcome the miniaturization barrier in scaled-down gas chromatography devices, the fundamental scientific conflict has to be resolved between the capacities of chromatographic separation and fluidic pumping under size restriction. Gas chromatography systems identify targets by racing them along a column resulting in spatial separation. Ideally a longer column provides farther isolation among more targets and thus higher detection capacity. However, it imposes rapidly-increasing fluidic resistance that requires over-sized pumps preventing true portability of the whole system. Therefore, in order to enable both high-capacity and wearable-portability in GCs, both the sufficient column length and fluidic head pressure should be attained in a miniaturized size. Currently there are no viable options to achieve both. This project proposes to address such barriers by: (1) investigating fundamental sciences and establishing a prediction model of the proposed novel gas chromatography configuration, (2) examining and maximizing performance capacity and limitation under scaling, and (3) experimentally demonstrating functioning GC operation utilizing the novel configuration for environmental monitoring: detection of volatile organic compounds (VOCs).

Intellectual Merit: Although holding great promises as an enabling tool, recent micro-scale gas sensors still require bulky pumping systems barring true portability of the whole integrated system. This project obviates such dilemma by providing a novel paradigm-shifting concept in gas-chromatography-based sensors. Scientific establishment of the proposed concept is expected to lead to a revolutionary advancement in generic chemical and biological detection technology and instrumentation in all scales. Additionally, the experimental demonstration will provide a new design guideline for the multiple-component gas chromatography system with the new configurations.

Broader Impact: Recent literature and government policy have increasingly reported the emerging demands of knowing environmental conditions in real-time at workplace, public, and home. The proposed project is expected to bring MicroSystems technology, analytical chemistry, and environmental education together creating synergetic impacts in increasing the environmental awareness in both academia and public. Specifically, the education objective of this project is to enhance the awareness of under-represented highschool and K-12 students of the importance in environmental monitoring and the roles of science and technology. This project will educate the next-generation students with the impacts of the micro/nano sensor technology in such a context. This project will train multiple graduate and undergraduate students through a new course and hands-on modules, and many K-12 students to the basic sensor concepts through on-going collaboration with a local science museum. This project is highly inter-disciplinary among engineering and science, and will also expose students to important social issues for balanced education.

Data are increasingly generated, stored, and processed distributively. Meanwhile, when large amounts of data are generated, ambiguity, uncertainty, and errors are inherently introduced, especially in a distributed setup. It is best to represent such data in a distributed probabilistic database. In distributed data management, summary queries are useful tools for obtaining the most important answers from massive quantities of data effectively and efficiently, e.g., top-k queries, heavy hitters (aka frequent items), histograms and wavelets, threshold monitoring queries, etc. This project investigates novel query processing techniques for various, important summary queries in distributed probabilistic data.

Broadly classified, this project examines both snapshot summary queries in static (i.e., no updates) distributed probabilistic databases, and continuous summary queries in dynamic (i.e., with updates) distributed probabilistic databases. A number of techniques are explored to design novel, communication and computation efficient algorithms for processing these queries.

A distributed probabilistic data management system (DPDMS) prototype is implemented based on the query processing techniques developed in this project. This DPDMS is released to and used in practice by scientists and engineers from other science disciplines as well as industry.

Graduate and undergraduate students, including those from minority groups, are actively involved in this project. Findings from the project have been integrated into different courses, demos, and educational projects. For further information, such as publications, data sets, source code, and education initiatives, please visit the project website at http://www.cs.fsu.edu/~lifeifei/dpdm.

This Faculty Early Career Development (CAREER) award provides funding to enable the cost-effective manufacture of nanostructures in a manner that is scalable to areas large enough for photovoltaic applications. The high cost of solar energy is the main impediment to its widespread adoption. Nanostructures hold great promise to lower this cost via enhanced light trapping and increased efficiencies. However, there exist no viable approach for the manufacture of complex nanostructures over areas large enough (~1m2) to be of interest in solar applications. This project aims to overcome these limitations via a massively parallel, optical approach that will enable fast nanopatterning with near-molecular resolution. When combined with inexpensive replication technologies, a new framework for scalable nanomanufacturing becomes feasible. Another intellectually compelling core of this approach is the demonstration that the 150-year old far-field diffraction limit can be overcome at low-light intensities. This project aims to: (1) study optimized molecule systems for optical nanopatterning, (2) assemble an optical system that is capable of fast nanopatterning, and (3) apply this system to build a solar cell, whose efficiency is enhanced using nanophotonic structures.

The ability to sculpt nanostructures over large areas with exquisite fidelity will advance fields beyond solar cells, especially in nanoelectronics and nanophotonics. This system will be made available to users in academia and industry, enabling early and widespread adoption. This project should lead to the creation of intellectual property and to commercialization with concomitant generation of high-value jobs. In order to integrate education with research, this project includes two novel demonstration modules in solar energy specifically designed to appeal to high school students and undergraduates. A primary component of the education effort is the integration of under-represented students in solar-energy research.

This project develops nonlinear statistical models and classification procedures for time-varying shape and investigates their application to biomedical image analysis problems. In biology and medicine it is often critical to understand processes that change the shape of anatomy. For example, a neuroscientist studying the development of the infant brain would be interested in how neurodevelopment is different in healthy children versus those with Autism. An evolutionary biologist studying how a species has evolved to adapt to its environment would be interested in studying changes in the shape of bones found in the fossil record. The challenge in this modeling problem is that shape and shape variations are highly nonlinear and high-dimensional, and standard linear statistics cannot be applied. Therefore, the ability to model and understand changes in shape depends on the development of new regression models for data in nonlinear spaces. The research activities of this project include: (1) developing statistical models for dealing with time-varying shape using least-squares principles in shape manifolds, (2) investigating new classification methods for shape sequences, and (3) validating the methodology using synthetic data and testing its efficacy for neuroimaging applications in Alzheimer’s disease and Autism. In addition to the significant impact to computer vision, biology, and medicine, this project is combining differential geometry, statistics, and computing within the undergraduate and graduate computer science curriculum.

This CAREER proposal aims to integrate PI?s research in bacteriophages with education and outreach. The motivations behind this CAREER proposal are three-fold: engineering, scientific and educational. The principal engineering goal of this CAREER proposal is to demonstrate the application of bacteriophage (virus that infect bacteria) mediated biocontrol in activated sludge systems using filamentous bulking and membrane biofouling in submerged bioreactors as the two model applications. The broad scientific goals are to: (1) to better understand phage mediated lysogeny of key activated sludge under the influence of various environmental and operational parameters: and (2) to study the phage diversity of the isolated phages from full scale activated sludge plant using 454 pyrosequencing. The educational goal is to enhance the participation of minority undergraduate and k12 students in environmental engineering using novel computer animation and internet based techniques, provide minority U.S. undergraduate students the international research experience and integrate the proposed research into education at various levels and at multiple institutes (University of Utah and the University of Texas Pan American, a Hispanic population serving institute at the U.S.-Mexico border). The specific research tasks are to: (1) isolate bacteria from the biofilm formed on the membrane of a laboratory scale membrane bioreactor and characterize these using molecular tools, (2) isolate lytic phages from full scale wastewater treatment plants with selected model filamentous bacteria and the bacteria isolated from the lab scale membrane bioreactor, (3) demonstrate phage mediated biocontrol of filamentous bulking caused by selected model bacteria and biofilm forming bacteria, evaluate the cross infectivity in bioreactor and environmental impact on receiving waters of isolated phages, (4) evaluate whether lysogeny is important in key activated sludge bacteria under the variations of pH, temperature, organic loading and toxic loadings, and in the presence of heavy metals using cultured model bacteria and, (5) obtain the genomes of isolated phages from tasks 1 and 2 using 454-pyrosequencing and study the genomes using established bioinformatic tools.

The PI?s educational and outreach aims are to: (1) involve undergraduate and high school students in laboratory research to stimulate their interest in environmental engineering, (2) integrate bacterial ecology and virology concepts into teaching to develop an effective learning module for undergraduates, (3) develop computer animation and web based tools for improving the public understanding of science, wastewater treatment and phage-related issues and, (4) integrate research into graduate education and disseminate the knowledge and research findings.

The proposed research will improve our understanding about the role of bacteriophages in activated sludge systems, the world?s most used engineered bioreactors. The research will develop phage mediated control strategies for filamentous bulking and membrane biofouling in membrane bioreactors (MBRs), the two most common operational problems in activated sludge bioreactors. Hence, the research promises to provide long term energy sustainability (i.e reduced air sparging in MBRs) and cost effectiveness to the operation of activated sludge systems including membrane bioreactors. Operational and environmental factors that triggered phage mediated bacterial lysis research, proposed in this CAREER proposal, is fundamental in nature and potentially sheds light on unknown reasons for the process upsets in activated sludge bioreactors. The proposed research, for the first time, will use fundamental concepts of virology to provide operational sustainability to activated sludge systems. This is the first systematic study to explore phage-bacteria interactions in activated sludge processes.

The research outcomes will directly affect many other related areas such as biofilm in drinking water distribution systems, understanding phage mediated horizontal gene transfer, elimination of hydrogenotrophic bacteria in biohydrogen producing reactors and nitrite oxidizers in anaerobic ammonia oxidation. The PI will focus on training of Native American and Hispanic students to encourage them to pursue careers in environmental engineering. Computer based animation and web based tools will help reach a broader audience. The PI?s unique effort to develop and teach an undergraduate course at the University of Texas Pan American will stimulate interest in Hispanic students to go for higher studies in environmental engineering. Graduate students will be trained to be leaders in their field as well as engineering ambassadors. Lab practices in k12 curriculum will expose k12 students to the exciting field of wastewater engineering and microbiology. Presentations at leading conferences and publications in peer reviewed journals of highest repute will demonstrate the success of the research.

Magnetic microrobots that navigate the natural pathways of the body have the potential to revolutionize minimally invasive medicine and biomedical research. Current magnetic manipulation systems utilize massive magnets to produce a uniform magnetic field over a relatively small area. Uniform magnetic fields are used to simplify control, but this simplified control comes at a huge cost, and it is difficult to scale up most laboratory field-generation systems to the size required for clinical use. The use of nonuniform magnetic fields makes it possible to place magnets nearer to the patient, which permits the use of smaller, less-expensive magnets, while simultaneously improving actuatable degrees of freedom and force levels that systems can render. The hypothesis being tested is that using nonuniform magnetic fields to wirelessly control medical microrobots results in superior systems?in terms of size, cost, and performance?compared to using uniform fields. This research consists of two thrusts: control of magnetically tipped continuum microrobots, which provide distal dexterity in hard-to-reach locations, and control of fully untethered magnetic helical microrobots, which swim and crawl through fluids, lumens, and soft tissue using a method inspired by bacterial flagella. Understanding how to use nonuniform magnetic fields for wireless control may be the key to translating nearly every previously developed method for microrobot propulsion into clinical practice. Magnetic microrobots may be the ideal platform from which to deploy the numerous BioMEMS devices and magnetic sensors and actuators that have been designed in recent years.

Collections of distributions arise naturally when analyzing large data sets. Since it is impractical to store all but a small fraction of such data, distributional representations are typically used to summarize the data in compact form. For example, a document in a corpus is typically represented by a normalized vector of frequencies of occurrence of keywords, an image is represented by a histogram over gradient features and speech signals are represented by spectral densities over a frequency domain.

Representing data sets as collections of distributions enables analysis via powerful concepts from statistics, learning theory and information theory. Concepts like strength of belief, information content, and pattern likelihood are used to extract meaning and structure from the data and are quantified using information measures like the Kullback-Leibler distance and its parent class, the Bregman divergences.

These measures capture meaning in data in a manner that traditional metrics cannot, by connecting abstract notions of information loss and transfer with concrete geometric notions like distances. However, they lack properties like symmetry and the triangle inequality that are essential requirements for the application of traditional geometric algorithms for data analysis.

In this project, the PI will develop a systematic, rigorous and global algorithmic framework for manipulating these distances. This framework will provide the foundation for efficient and accurate data analysis of spaces of distributions, and will lead to deeper insights into analysis problems across a wide range of applications.

The objective of this research is to develop high-rate data links (>20 Mb/s) for implanted biomedical devices that can operate in the presence of narrowband interference from an inductive power link. The approach is to employ ultra-wideband signaling with transmitted reference synchronization to realize low-power, high-rate data transfer over the short distances required by biomedical implants. A comprehensive approach to system design is employed, with substantial effort focused on the design and modeling of the antenna and channel so that their effects can be accounted for in the circuit design.

The novel ultra-wideband transceiver architectures being explored in this work will bring about an order of magnitude increase in data rates for biomedical implants, as compared to the narrowband transceivers that are currently prevalent. This research will advance the state of the art in low-power, short-range wireless communications, and is expected to prove beneficial for a range of applications beyond implantable devices.

The high-rate data links being explored in this research have the potential to be of tremendous benefit to society, by enabling biomedical devices that can improve the quality of life for individuals (e.g. visual prostheses, neural control systems for prosthetic limbs) and by enabling extensive, long term neural recordings that will further our understanding of the brain’s physiology. The educational initiatives integrated with this research target every stage in the development of young engineers to solve tomorrow’s technology challenges, from high school outreach initiatives, to undergraduate research involvement, to graduate course curriculum development.

The Analytical and Surface Chemistry (ASC) program of the Division of Chemistry will support the CAREER development plan of Prof. Ling Zang of the Department of Chemistry and Biochemistry at the University of Southern Illinois. Prof. Zang and his students will synthesize organic nanowires and characterize their optoelectronic properties using near field scanning optical microscopy (NSOM) and conductivity measurements. The study will result in increasing understanding of the behavior of adsorbates on organic nanowires and the electronic response of organic nanowires due to adsorption of molecules on their surface. The study will facilitate the development of improved nanowire-based sensors that can find use in many applications including environmental analysis, bioanalytical measurements and defense and national security applications. The project will provide excellent educational training opportunities to students in the area of nanomaterials synthesis and will address growing workforce needs. Particular emphasis will be placed on recruiting high school students to this new field.

The PI’s goal in this project is to advance the state-of-the-art of haptics research, which has to date centered primarily on the use of point-based force-feedback devices, by exploring and comparing two novel approaches to providing haptic guidance for path following and fine motor tasks. These two approaches are: (1) using tactile shear guidance to provide directional information through the grip of a stylus; and (2) augmenting a traditional stylus-based haptic interface with an active handrest. In the first approach (providing directional information through tactile shear feedback), the PI will investigate using a specialized stylus interface with shear devices embedded in its grip. These devices will transmit shear feedback to the user’s thumb and index finger. The second approach (using an active handrest) for executing path following and fine fingertip motions was inspired by the way artists use a baton-like handrest to support fine hand motions during detailed painting. The active handrest will be explored as a supplement or substitute for traditional force feedback and other haptic guidance techniques, such as virtual fixtures. Through modeling and human subjects testing, the PI will investigate two modes of supporting the user’s wrist and/or forearm while gripping a traditional stylus haptic interface. One mode will have the handrest impart forces or motions to the user’s wrist/forearm, providing corrective task intervention. The second control mode will infer the user’s optimal handrest position and preemptively move itself to provide continued support based on measured reaction forces. The PI will evaluate and compare the impact tactile shear guidance and the active handrest have on task performance (e.g., accuracy and execution time), versus established approaches. The research will also produce theoretical characterizations of the passive dynamics between the forearm and hand that will form the foundation for controlling active handrest systems. Algorithms for controlling the handrest under multiple modes of operation will be established.

Broader Impact: This research will lead to dramatic improvements in the realism of simulations and virtual environments of all kinds. Project outcomes will be applicable across a broad cross-section of domains including neuro- and tele-surgery, hand rehabilitation, guidance systems for the blind, and consumer applications like automotive GPS navigation systems. Imagine if, rather than having to look at your GPS navigation map or listen to its instructions, you received a shearing tactile cue from the steering wheel that told you a turn was coming up; this could significantly reduce driver cognitive load and thereby lead to improved driver safety. A major objective of the PI is to attract women and underrepresented students, especially Native Americans, into the fields of science and engineering. To this end, he will develop haptic learning modules based on his research interests, which can be presented in conjunction with established college-wide outreach activities aimed at junior high and high school students, and that can also be used by the University of Utah Robotics Group (with which the PI is affiliated) as part of its established relationship with Montana State University (which has a large Native American representation in its undergraduate programs). The PI will also develop a course in haptics with innovations such as a Haptics Concept Inventory and hands-on demos.

Workflow-based systems have emerged as an alternative to ad-hoc approaches to data exploration that are widely used in the scientific community. Workflows can capture computational tasks at various levels of detail and systematically record the provenance (history) information necessary for reproducibility, result publication and sharing. Although the benefits of using scientific workflow systems are well known, the fact that workflows are hard to create and maintain has been a major barrier to wider adoption of the technology in the scientific domain.

The goal of this project is to produce new algorithms and techniques for exploring and re-using useful knowledge embedded in workflow specifications and in the provenance of the data they manipulate. This project addresses key limitations in existing workflow systems. First, it develops a set of usable tools that enable casual users (who do not necessarily have programming expertise) to perform exploratory tasks and solve problems through workflows. These include intuitive user interfaces to manipulate collections of workflow and to query workflows by example. Second, it builds a scalable provenance management infrastructure to support the efficient execution of these operations.

The research results of this project advance the state of the art and build fundamental knowledge in storing, querying, and re-using provenance of computational tasks. This project has the potential to impact a variety of applications where the creation and maintenance of workflows is currently a major bottleneck. This includes large computational science projects and portals. Furthermore, it makes workflows and workflow technology more accessible to casual users. Through our interdisciplinary collaborations, this project will have immediate impact in helping improve the scientific discovery process. The involvement of graduate and undergraduate students in the project will provide mentoring opportunities. The PI is committed to recruiting minority students. The results of this project will be disseminated as research papers and as freely available tools at the project website: http://www.cs.utah.edu/~juliana/projects/NSF-IIS-0746500

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Recent advances in semiconductor technology have facilitated the realization of a host of new electronic devices with ever-decreasing dimensions. Handheld pocket computers (palm-tops), ultra-thin cell phones with internet, iPods, iPhones and micro-cameras are a few examples that exploit and adopt the advances in the technological development. However, as the typical component dimensions approach the nanometer scale, further miniaturization becomes increasingly difficult. It is believed that any further improvement in device functionality will require a transition from the conventional electronics to an altogether new regime known as “Spintronics.” While the electronic devices utilize the charge of electrons, the typical spintronic devices exploit both charge as well as the spin (a magnetic attribute) of an electron. Because of this additional attribute, spintronic devices are expected to be faster, smaller and consume less power than the conventional charge-based electronic devices. However, the spintronic devices can not be fabricated simply by making use of the simple semiconductors. The practical realization of spintronic devices heavily rely on the development of two new classes of materials namely, Dilute Magnetic Semiconductors (DMS) and Dilute Magnetic Dielectrics (DMD). These materials make it possible to utilize the electron’s spin in addition to its charge. Though a significant amount of work has been performed on DMS materials, very little has been done on DMD materials. This CAREER project will be focused on discovering new families of DMD materials that potentially can lead to innovation in spintronics. Educational program will develop numerous opportunities for graduate, undergraduate and k-12 students and teachers. Summer program will provide k-12 teachers more reasons to teach science with contagious enthusiasm in the classroom. Proposed work on introducing science and engineering to minority students will have meaningful societal impact.

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The integrated research and education goal of this Faculty Early Career Development (CAREER) project at the University of Utah is to discover new families of Dilute Magnetic Dielectrics (DMD) that will lead to innovation in Spintronics and to communicate materials science and engineering to a wider audience through science exhibits, lab-integrated courses, and hands-on activities. The most critical step in the functioning of a spintronic device is the injection of spin-polarized carriers at the ferromagnet-semiconductor interface. Recent studies have shown that dilute doping of semiconductors or dielectrics with magnetic atoms can provide an enabling breakthrough in achieving high spin-injection efficiency. This has led to an extensive effort exploring the possibility of inducing room temperature ferromagnetism in several systems. Most of the work in this field is still focused on dilute magnetic semiconductors. Little work has been performed on DMDs. This project will start an extensive research program to explore the possibility of inducing room temperature ferromagnetism in Rare Earth Oxide based high-k dielectrics by dilute doping of transition metal elements. The educational component of this project will disseminate the fundamentals of materials science and engineering to a wider audience. The following specific tasks will be performed: (i) developing interactive materials science exhibits for the Utah Science Center Museum, (ii) initiating a summer research program for k-12 teachers and students, (iii) and creating a collaborative and interdisciplinary environment for undergraduate and graduate research.

Intellectual Merit: This research focuses on the development of new technologies to ?see? through walls into buildings to show interior structures and the motion of people within the structure. Rather than relying on a single self-contained short-range radar, this method uses a large-scale network of low-cost sensors as multi-static radio frequency (RF) radars whose pair-wise and spectral measurements can be used to image the environment. This research lies at the intersection of statistical signal processing and radio propagation and addresses the necessary key advances related to dense networks of RF sensors and accurate statistical channel models. The proposed research (1) uses extensive measurements to develop valid statistical channel models that depend on the attenuation field, (2) develops and tests estimation algorithms for radio tomographic imaging, and (3) analyzes their estimation performance.

Broader Impact: If successful in leading to new tomographic environmental imaging systems, the proposal has the potential to significantly benefit fire fighters, other first responders, and building occupants in emergency situations. In addition, the research has the potential to benefit other types of communication networks by advancing cooperative spectrum sensing in dynamic spectrum access radio networks and improving channel simulation in multi-hop networks. The project is a crucial part of the principal investigator?s goal of integrating research and education in signal processing and wireless networks. This project will lead to a new wireless communication system laboratory, a key part of a departmental curricular initiative to provide students with integrative lab experiences. Further the project will develop and disperse new interactive modules to be used with students in grades 10 through 12, in particular in programs targeted towards students from under-represented groups, both part of department goals to increase the diversity and the total enrollment of students in electrical and computer engineering. Undergraduate student research will also be integrated into this project.

Future microprocessor chips will contain numerous computational cores, large cache hierarchies, and complex on-chip networks between cores and cache banks. For an application to exploit a processor’s peak throughput, it will have to necessarily be composed into many threads. As part of this project, the curriculum at Utah will be revised so that graduating students have the skills to write efficient multi-threaded programs that can harness the compute power in future processors. When multi-threaded applications execute on a chip, different threads and data transfers make varied demands on the hardware in terms of speed, bandwidth, power, reliability, etc. By optimizing specific cores and networks on the chip for different metrics, the hardware can meet the diverse needs of software. A processor that packs in heterogeneous functionalities and device characteristics will likely allow processor throughput to continue its steady rise while not compromising reliability or power-efficiency. This project explores the effect of optimizing on-chip networks for either speed, bandwidth, or power. It also explores the effect of customizing cores to execute the operating system, redundant threads, or speculative threads.

In recent years, the use of multiple antennas at both transmitter and receiver ends of a communication link has been identified and widely studied as the most practical method of increasing channel capacity. For the next generation cellular and wireless local area networks, multiple-input multiple-output (MIMO) technology that employs multiple antennas is envisioned to be the core technology to achieve higher data rates.

While MIMO technology promises significant information-theoretic capacity gain for wireless links, there are still many unknowns as to how to efficiently realize such gains in practical communication systems and networks. There are a number of key issues from the physical layer to the network layer that need to be addressed. This proposal aims to take a cross-layer approach to address these issues to facilitate efficient utilization of multiple antennas in wireless networks. MIMO detection is the most fundamental issue in MIMO networking, and it is the complexity bottleneck that limits the employment of MIMO technology. A main objective of this proposal is to develop low-complexity MIMO detectors that scale well with antenna number and modulation size so that it is applicable for practical network setting. We propose a novel MIMO detector based on the Monte-Carlo Markov chain (MCMC) approach which shows performance superior to other existing MIMO detectors at a complexity that is more than one order of magnitude less. Performance analysis of the MCMC detector and its impact on code design will be investigated. One primary focus is on joint optimization of channel codes with MIMO detection for large antenna systems. We plan to develop joint coding design and detection strategies to find capacity-approaching channel codes at high spectral efficiencies. Code design criterions will be derived for short channel codes that are suitable for delay-sensitive applications.

From the network layer this proposal addresses the issues of multiple access and resource allocation for MIMO wireless networks. A central issue in these designs lies in the amount of channel state information (CSI) available at the transmitter. We propose to study practical power control and scheduling algorithms that are robust to channel variations and have the capability of supporting limited CSI. We will address fairness and quality of service for users with heterogeneous channel conditions. Optimal signaling design for practical MIMO detectors will be investigated in order to maximize network throughput and minimize multi-user interference. These are closely tied with our study on the physical layer issues of MIMO detection and coding.

Broader Impact:

The educational plan of this project offers diverse opportunities to students at all levels. The proposed research will generate a cluster of undergraduate research projects, which in particular will focus on developing a multiple-antenna test bed for wireless local area networks. The PI plans to encourage students from under-represented groups to participate in such projects. The proposed research may generate industrial interest that can result in undergraduate industry sponsored projects. The proposed research will also attract graduate students to explore modern communication theory and encourage their future careers in this exciting field. The PI plans to develop a new course on software-defined radio (SDR) for wireless communications, and a more advanced course on cross-layer design for wireless networks at the graduate level.

Intellectual merit:

The intellectual merit of this proposal lies in the development of new techniques and theories in MIMO networking. The broader impact is in the interdisciplinary dimensions of this research, as well as in the educational program and the exposure of students in all levels to the proposed areas. This plan offers strong integration of the research with education and industry. The impact of this research is expected to be on a variety of fields, including coding and information theory, signal detection and estimation, algorithm design and complexity, network protocol design and more.

Digital designs that implement polynomial arithmetic computations are found in many practical applications, such as in Digital Signal Processing (DSP) for audio, video and multi-media applications. The growing market for such designs requires sophisticated CAD support for analysis and verification. Contemporary verification technology – mostly geared towards control-dominated applications – is unable to efficiently model and validate designs with large arithmetic datapath component. Such designs described at register-transfer-level (RTL) perform polynomial computations over bit-vector variables that have pre-determined word-lengths. Conventional Boolean models do not scale well wrt increasing word-lengths. To overcome this knowledge and technology gap, this research explores an altogether new paradigm for RTL datapath verification by incorporating symbolic computer algebra within a CAD-based verification methodology.

A bit-vector of size m represents integer values reduced modulo 2^m. Therefore, bit-vector arithmetic can be modeled as algebra over finite rings, where the bit-vector size dictates the cardinality of the ring. The verification problem then reduces to that of proving polynomial equivalence over finite rings of residue classes Z_{2^m}. In this project, the investigator: (1) models RTL datapaths as polynomial functions over finite integer rings of the type Z_{2^m}; (2) Studies the properties of such class of rings for polynomial equivalence using number theory and ideal theory; (3) Derives algorithmic solutions to RTL datapath verification using symbolic and algebraic manipulation; (4) Investigates the impact of polynomial manipulation over Z_{2^m} on RTL datapath synthesis; and (5) Investigates how to model arithmetic with imprecision (e.g., error rounding and saturation arithmetic) as polynomial functions. The intellectual merit of this research lies in its mathematical challenge and in its engineering application to digital design verification. Successful completion of this project would broadly impact datapath verification theory and practice and would also enhance the understanding of some classical mathematical problems. Both graduate and undergraduate students will be involved in this research. The results will be disseminated not only to the Digital Design and CAD community, but also to the Symbolic Algebra community.

CAREER: Vertically Integrated Program Analysis for Embedded Software In recent years, a great deal of progress has been made towards tool support for developing embedded software. Tools solve a variety of difficult problems, for example by automating error-prone implementation tasks, by eliminating redundant and inefficient constructs, and by guaranteeing the absence of certain classes of errors, such as race conditions or out-of-memory exceptions. This NSF CAREER research is about Vertically Integrated Program Analysis and Transformation (VIPAT), a new way to look at embedded software tools: as a collection of building blocks that can be connected together in different ways to support novel analyses and transformations. The existing tools become mechanisms that are controlled by a high-level policy. VIPAT is based on two main ideas. First, the vertical integration of tools that operate at various levels of abstraction, which permits high-level transformations to be precisely targeted at parts of a system whose low-level resource usage is worst. Second, a clean separation between mechanism and policy, enabling effective reuse of existing tools in new situations. This research is a step towards a world where meaningful static guarantees about program behavior can be made, and where software can be automatically specialized to meet platform- and application-specific requirements such as time and energy constraints. The high-level vision is “fearless reuse”: developers should spend less time worrying about resource usage and potential failure modes of components that they reuse.

Heart disorders are a malady, which affect many Americans each year. Although techniques such as electrocardiography allow physicians to postulate as the probable cause of patient discomfort, cardiac source localization cannot currently provide the physician with the precise location within the heart of a bioelectric abnormality, nor can current techniques provide the physician with confidence measures based upon the numerical (discretization) errors, modeling errors and variability/uncertainty errors which exist in the inverse problem. This research involves the development of methods for quantifying and controlling error and uncertainty in computational inverse problems. The specific driving application is to make the computational source localization procedure a viable tool for diagnosing cardiac bioelectric field problems. This research is valuable for both its multi-disciplinary influence and its expansion of computational science and engineering (CS&E) techniques beyond the original applications for which they were designed. The academic merit of this research is its fundamental contribution to the solution of computational inverse problems and its practical contribution to the bioengineering problem of cardiac source localization. In the true spirit of CS&E, this research is the synergy of a domain specific task and computational science tools. The broader impact of this research results from its extendibility to a much larger class of computational inverse problems. The educational objectives of this proposal are focused on training young scientists to properly view simulation science as a tool in the validation of and extension of scientific inquiry.

Specifically, this research is partitioned into two aims: (1) to quantify and minimize the effects of numerical modeling errors in the ECG source localization computation through the judicious use of high-order methods and the discontinuous Galerkin method; and (2) to quantify and minimize the effects of uncertainty and variability in the source localization process through the exploration of the polynomial chaos methodology for uncertainty quantification.

The purpose of this research is to develop several unexplored areas in data compression, as well as to utilize universal data compression techniques in other applications including biological modelling and a novel direction of joint source-channel coding. The research focuses on four topics: (a) design of joint source-channel universal source code based codes, (b) study of universal compression for large and unknown source alphabets, (c) design of advanced universal coding techniques for non-traditional, yet more realistic, data models with practical implementations, and (d) the study of random access lossless compression. Common techniques in joint source-channel coding suffer from severe synchronization problems in bad channel conditions and do not address universality issues when the source statistics are unknown. This research develops techniques to combat these problems, and even attain “free” gain in channel decoding performance for redundant channel information streams. Common compression schemes assume that the data is from a known alphabet, it has a “standard” stationary or constantly changing statistical model, and it consists of a long sequence. However, (a) there exist compression applications with large unknown alphabets, such as text compression where the words constitute the alphabet, (b) most real data sequences are usually neither stationary nor of constantly varying statistics, and (c) random access is necessary in large compressed data bases. The investigator studies these three non-traditional problems. The research work combines the development of rigorous theoretical results including redundancy and description length bounds, with empirical testing, algorithm design with focus on practical low-complexity techniques, and implementation of proposed techniques. Finally, the research also investigates the use of universal compression techniques to segmentation and modelling of biological sequences.

Under this CAREER Award, methods from theoretical and computational mechanics will be combined with pattern theory to directly incorporate medical image data into the analysis of deforming biological tissues. Results will provide new finite-element based tools that use image data to track three-dimensional kinematics and nonlinear strain in deforming tissues and to register anatomical structures appearing in image data sets. Two applications would be targeted: in vivo measurement of strains in the beating human heart and in situ measurement of strains in ligaments. The techniques and resulting software, which will be made available to the public, are expected to be applicable in numerous other areas including geophysics, manufacturing engineering design, biology and computational medicine.

The educational component focuses on three areas: bioengineering outreach to Utah high school students through a summer institute; developing an integrated biomechanics curriculum built around three core courses, and training undergraduate and graduate students in conjunction with research objectives.

There is a great demand for technologies that enable neuroscientists and clinicians to observe the simultaneous activity of large numbers of neurons in the brain. The monitoring of these groups or “neural ensembles” allows researchers to begin to understand the cooperative mechanisms used by neurons to encode and process information. Recent advances in MEMS technology have produced small arrays of microelectrodes containing as many as 100 recording sites. “Next generation” neural recording systems must be capable of observing 100-1000 neurons simultaneously, in a fully-implanted unit.

While integrated electronics have been developed for small-scale amplification of the weak extracellular neural signals (<100 electrodes), existing circuits have high levels of noise and consume too much power to be fully implanted in larger quantities. We propose to develop low-power, low-noise analog and mixed-signal VLSI systems allowing fully implantable recording of 100-1000 neurons.

A fully implanted multichannel neural recording system must use an RF or inductive-link transmitter for transcutaneous telemetry. We will investigate techniques for on-chip data reduction (e.g., spike thresholding, feature detection) to assist in spike sorting and reduce the required bandwidth (and hence power) of such a transmitter.

The educational component of the proposed work involves the improvement of the VLSI curriculum in the PI’s department. This improvement will consist of three main thrusts: (1) Development of a laboratory component of a course in analog integrated circuit design taught by the PI. The construction of “class chips” will allow students to measure VLSI circuits in modern submicron fabrication technologies. (2) Development of a new advanced analog VLSI course. (3) Enlisting industrial partners to evaluate our VLSI curriculum. In addition to this curriculum development, the PI will also mentor a graduate student who will perform research related to the proposal.

Research world-wide on biosensing is motivated by numerous applications in environmental and food testing and clinical diagnostics, for example. However, the important problem of detecting in parallel a large number of molecular species from the very small samples typical of most collection procedures remains an elusive goal. This CAREER research plan focuses on solving this problem by merging the science of nanophotonics with waveguide biosensors and microfluidics for the development of a new class of molecular detection array.

The immobilization of metallic nanoparticles onto discrete zones of an optical waveguide surface makes the parallel detection of a large number of molecular species feasible. In each zone, capture molecules tethered to the nanoparticles preferentially bind to a particular molecular species through an affinity interaction. Strong localization of light about each nanoparticle allows for dramatic improvement in optical signal transduction, thereby facilitating the detection of small numbers of molecules bound within each zone.

Microfluidics will be used to deliver small sample volumes to each sensing zone and passive mixing structures will be studied in order to increase the molecular binding probability within each zone.

The education plan focuses on the creation of a summer optics workshop for secondary school physics and science teachers. As more demands are placed on teachers, and as technology continues to advance at a rapid pace, teachers need a way in which to further their knowledge of science and hands-on teaching methods. Detailed lesson plans and laboratory exercises will be developed for deployment in the classroom, with the goal of improving student understanding of and instruction in optics and the sciences, and encouraging students to pursue careers in engineering and science. Participation of teachers from Hispanic and Native American schools will be strongly encouraged.

This project addresses the question of how to automatically generate 3D computer models of objects and scenes using data from a range finding device, such as a laser range scanner, sonar, ultrasound, or radar. Such 3D computer models are important in a wide range of applications including defense surveillance, forensics, teaching, and medicine. Range measuring devices typically sweep a beam of energy to gather many millions of 3D measurements from surfaces of objects but they have some limitations. First, because not all object are visible from a single point of view, a single sweep is incomplete. Second, each individual range measurement is not necessarily accurate because the measurement process is inherently noisy. The strategy is to systematically fuse together many measurements from different points of view in order to create accurate, complete 3D models. This project examines some of the fundamental mathematical questions pertaining to this process and then studies how to implement and demonstrate this theory on real data.

Range-finding devices measure distances to objects by reflecting energy off of the interfaces between different types of materials, but they provide a noisy, mathematically complex, and highly nonlinear transformation from a collection of surfaces to a set 2D depth maps. This project will develop statistical methods for estimating manifolds from this kind of data, thereby generalizing the current state of the art in estimation theory, which is primarily concerned with estimating functions or fields. Thus, the goal is to provide a general, complete, and practical foundation for 3D surface reconstruction. The strategy is to find the surface that maximizes the posterior probability conditional on a collection of range measurements taken from different points of view. The reconstruction framework is Bayesian; it includes a sensor model as well as prior knowledge about the characteristics of the object or scenes being modeled. This work will address a number of important issues pertaining to this statistical methodology for building 3D models, including better sensor models, high-order priors, fast and robust algorithms, and broader applications. These developments will comprise a fundamental scientific result: the generalization of the basic principles of estimation theory to the challenging and timely problem of 3D surface reconstruction.

The focus of the proposed research program is on the development of sensing technology and model-inversion based identification methods to infer online the molecular weight distribution (MWD) of polymer melts based on broad-band dielectric measurements. The ultimate goal of the research is to develop new polymer processing technology for online customization of the properties of the final product by varying the processing conditions during extrusion and molding. The inverted fringe-effect microdielectric sensing with controlled depth of field penetration is a novel approach for measuring spatially resolved properties of a material in a direction normal to the interface. In the proposed approach, methods for inferring MWD online from dielectric measurements will be based on theoretical modeling of polymer relaxation in electromagnetic fields and on statistical correlation methods. Theoretical and experimental studies will be followed by the development of advanced process control systems, which will enable online polymer customization by varying conditions during processing. The educational program is aimed at creating a balanced undergraduate process control curriculum, which includes project-based hands-on experience in implementing practical control systems in laboratory settings.

This research aims to develop a conceptual natural language processing (NLP) system with adaptable components that can be easily tailored for different domains and applications. The architecture of the system consists of fine-grained layers to support various depths of text processing. The shallow layers support syntactic processing, which may be sufficient for some information retrieval tasks, while the deeper layers support semantic and conceptual processing for in-depth language understanding. The system includes components for part-of-speech tagging, prepositional phrase attachment, semantic feature identification, and concept extraction. Each component can be tailored for new domains with minimal manual effort. The layered architecture also allows students to develop individual components and plug them in to the larger system for experimentation. The education goals are to use the system as the basis for a hands-on science workshop for young girls, for summer lectures to high school students, for class projects in natural language processing and machine learning, and for graduate and undergraduate research projects. The purpose of the research is to develop techniques for building conceptual natural language understanding systems automatically or semi-automatically for new domains. Generating conceptual sentence analyzers quickly and efficiently is an important step toward many practical applications, including conceptual information retrieval, text categorization, and information extraction.

CTS – 9624907 Russell Stewart University of Utah ABSTRACT The project is on the fabrication of a microanalytical separation device incorporating the microtubular motor protein (kinesin) into nano-fabricated machines. A prototype active chromatography device will be built to recognize, separate and detect specific DNA fragments on a single micromachined chip. A fluorescent-labeled DNA fragment in solution will attach selectively to the motor protein and move along aligned microtubules in a microchannel to a detector. The potential impact of the project is strong in bioseparations and chemical process monitoring. If successful, it may be possible to mimic intracellular transport in fabricated machines. The educational plan includes development of a new lecture and two laboratory courses on protein engineering and microfabrication. Students will be trained to apply biological principles to conventional engineering problems.