Presidential Early Career Award for Science and Engineering (PECASE)
The world is becoming increasingly dependent on complex interconnected systems, such as smart building management, multi-vehicle systems and convoys, irrigation networks, large array telescopes, and the power distribution grid. The advent of these systems has created a need to design and analyze controllers that can observe information from only a small portion of a network but may ultimately affect a large portion of the network. This includes, and is a key challenge in many problems with cyber-physical systems. Conventional controls analysis assumes that one centralized decision-maker can access all available measurements, and determine the usage of all possible means of actuation. Most methods of design and analysis are extremely fragile to this assumption, and break down when such centralization is not possible or is not desired, leading to the field of decentralized control. Dr. Rotkowitz has has made pioneering contributions in the decentralized implementable control of massively interconnected systems and will continue to do so through the PECASE.
The PECASE is the highest honor bestowed by the federal government on science and engineering professionals in the early stages of their independent research careers. The awardees come not only from academia but from federal labs and agencies as well. Dr. Rotkowitz’s award was one of 19 that were nominated by the National Science Foundation.
IDIES Seed Funding Award
Johns Hopkins Discovery Award
ARO: Breaking the square-root barrier in covert communications
ONR: SEA-STAR: Soft Echinoderm-Inspired Appendages for Strong Tactile Amphibious Robots
Associate Professor Derek Paley (AE/ISR) is the principal investigator for a $2 million grant from the Office of Naval Research’s Basic Research Challenge Program. Co-principal investigators on the “SEA-STAR: Soft Echinoderm-Inspired Appendages for Strong Tactile Amphibious Robots” grant are Aerospace Engineering Chair Norman Wereley (AE), Associate Professor Carmel Majidi (Carnegie Mellon University), Senior Research Scientist James Weaver (Harvard University), and Professor Robert Wood (Harvard University).
The researchers will create soft underwater robot appendages that mimic functionality found in sea stars, brittle stars and basket stars. These animals are known as “radially symmetrical echinoderms.”
The long-term goal of the SEA-STAR project is to develop a functionally hierarchical architecture and distributed control scheme for the robot appendages that will give them dexterity and allow them to operate with a high force-to-compliance ratio. The hierarchical design will be inspired by the complex organization seen in the echinoderms---endoskeletal elements, water vascular systems, and tube-feet arrays.
The SEA-STAR robotic appendages will be controlled by a network of embedded sensors and hydraulic actuators. These will provide shape proprioception (grasping) and local closed-loop control. The researchers have combined expertise in echinoderm anatomy, soft and bio-inspired robotics, the mechanics of materials and tribology, multi-material 3D printing, and distributed sensing and control of underwater robotic systems.
The ONR Basic Research Challenge Program was established to competitively select and fund promising research programs in new areas. The program stimulates new, high-risk basic research projects that have naval relevance with the hope of attracting new investigators to the Office of Naval Research.
NSF: A Unified Framework for 3D CPU Co-Simulation
Professor Ankur Srivastava (ECE/ISR) is the principal investigator for a National Science Foundation SI2-SSE 3DSIM grant, “A Unified Framework for 3D CPU Co-Simulation.” Professor Bruce Jacob (ECE) is the co-principal investigator.
The three-year, $500K grant will allow Srivastava and Jacob to develop a full-system simulator for 3D CPUs that accounts for the architectural and physical interactions between the cores and memory components. This will allow the co-simulation of power, performance and reliability characteristics.
The project will address chip design issues that have come to the fore in recent years. Performance enhancements and increased energy efficiency that previously could be obtained by reducing the dimensions of transistors are becoming more difficult to achieve. Thus, Moore's law no longer holds true for conventional approaches to chip design.
Three-dimensional (3D) integration of chip components has emerged as an innovative packaging alternative to conventional approaches where multiple layers of silicon are stacked and interconnected using directly through the silicon layers (this technique is known as "Through Silicon Via" or TSV). Using TSVs and 3D packaging enables significant benefits to the performance, functionality and energy efficiency of future CPUs. However, 3D integration results in new types of interaction patterns between computing cores and between core and memory components. In addition, the close proximity between cores and memory causes their physical attributes, such as their temperature, noise of power delivery, and reliability to become uniquely interdependent. If innovations in 3D integration are to continue, substantial investment in frameworks that can simulate and evaluate 3D computer architectures are necessary.
This project seeks to develop such a simulation framework and make it available to the computer architecture design community. The researchers’ framework will support a wide array of 3D CPU configurations, including intricate specifications of cores, core counts, network on chip protocols, on-chip/off-chip caches, main memory and off-chip secondary storage (built using diverse set of devices including SRAM, DRAM, non volatile devices). The project is a substantial addition to the repertoire of 3D integrated circuit design and simulation frameworks and will play a vital role in future innovations in 3D CPU architectures.
NIST: Silicon Physical Unclonable Functions (PUFs) as an Entropy Source
The U.S. Department of Commerce and the National Institute of Standards and Technology (NIST) have partnered to grant Professor Gang Qu (ECE/ISR/MC2) approximately $100,000 to study the use of Silicon Physical Unclonable Functions (PUFs) as an entropy source.
Cryptographic keys play a vital role in modern cryptography and almost all security applications. A short key is easy to break, but a longer key does not guarantee better security. For a key to be strong, it must be random and unpredictable, which can be measured by entropy. In this project, Dr. Qu will investigate whether the randomness in silicon fabrication variation can be captured and used as a source to generate entropy and to enhance the quality of other entropy sources.
Highly Conductive, Robust, Corrosion-Resistant Nanocarbon Current Collectors for Aqueous Batteries
We propose to develop flexible, robust and corrosion-resistant nanocarbon current collector for aqueous battery applications. The nanocarbon film made of functionalized few-walled carbon nanotubes (FWNTs) and polymers is highly conductive, thin and mechanically strong. FWNTs will be grown by chemical vapor deposition (CVD) with powder catalysis. The nanocarbon film can be fabricated with scalable processes. FWNTs allow us to selectively functionalize the outer walls without decrease the high conductivity inner walls, much better than single-walled carbon nanotubes. We will investigate two structures; one is polymer on FWNTs (P-on-NT) and the other one is FWNT on thin polymer textile fibers (NT-on-P). In both types of FWNT-polymer films, the nanotubes contact each other directly for fast charge transport. The polymers crosslinked with FWNTs provide enough mechanical strength and stability in aqueous electrolytes. The use of FWNTs and the unique structure will allow us to achieve both high DC conductivity and excellent mechanical strength, which are critical for current collector applications but not available yet.
We will also investigate the nanocarbon films as current collectors in aqueous batteries with different pHs, using Pb acid and NiMH batteries as the two testbeds. We will study the DC conductivity, mechanical strength and ampacity in both dry and wet films.
The newly developed nanocarbon current collectors can be applied to a range of aqueous batteries and be extended to other battery chemistries.
This is a one-year, $250K grant.
ARO Special Programs: Building Robust and Practical PUFs with Configurable Ring Oscillators
The Adaptive Auditory Mind: Role of Rapid Plasticity and Temporal Coherence in Auditory Scene Analysis
The research is fundamentally interdisciplinary, at the interface between cognitive sciences, neurophysiology, and computational neuroscience. It promotes a theoretical framework that spells out how perception arises from interactions between cognitive influences and stimulus via a rapid-adaptive process at the neuronal level. This frame work guides all modelling and experimental data interpretation, and has clear implications to sensory perception and multimodal interactions. The key challenges lie in the three fields of neuroscience, psychoacoustics, and computational neuroscience as follows. The fundamental hypothesis of this research is that a rapid-adaptive process alters neuronal circuits and selectivity during perception of sound, and that this plasticity is enhanced by the existence of a temporally coherent structure in the acoustic stimuli. This hypothesis will be thoroughly investigated and adopted into the architecture of current computational models of auditory processing and sound streaming. Application of this model, especially in speech segregation and enhancement will be addressed to demonstrated the validity of these ideas for mimicking human abilities.
This project is organized around three specific aims, each composed of several projects. AIM I: Using ambiguous percepts to explore rapid plasticity. AIM II: Role of stimulus coherence in pattern formation. AIM III: Tying it all together. Computational models of streaming with complex signals.
This is a five-year, $163K grant.
Computing and Communication Foundations: Coding and Information - Theoretic Aspects of Local Data Recovery
This project studies fundamental problems in data coding that can improve the efficiency of distributed storage systems by increasing data reliability and availability while reducing storage overhead compared to existing industry standards. The results of this research can benefit storage applications ranging from financial, scientific monitoring, and signal processing to social networks and sharing platforms. The new combinatorial, coding, and information theoretic tools developed in this project will be incorporated in course curricula in the respective institutions of the principal investigators.
Data coding with locality, the focus of this project, is a rapidly developing area of coding theory that was initially motivated by applications in distributed storage, and has links to many areas of network science (e.g., index coding and network coding) as well as to computer science. This project advances the theory and practice of data coding with local recovery by investigating broad implications of the locality constraint in coding problems. These include studying new error-correcting code families and their decoding, fundamental limitations on the code parameters and capacity bounds under the requirements of local data recovery. The newly designed coding schemes developed in this project will be validated through implementation and evaluation in simulated computer environment, aiming at enhanced performance of data coding in current industry solutions.
This is a three-year, $250K grant.
Integrated Bidirectional Power Electronic Charger/Converter for Plug-in Electric Vehicles
This PFI: AIR Technology Translation project focuses on translating an integrated bidirectional onboard charger and dc/dc converter technology to fill the need for compact and efficient power converters for plug-in electric vehicles. The proposed technology is important because it reduces the weight, volume and cost of onboard converters, while enhancing their efficiencies, and enabling bidirectional operation. The successful completion of this project will facilitate widespread adoption of electric vehicles, and lead to the creation of jobs through the small business partner once the technology matures toward commercialization. The project will result in a prototype of an integrated charger/converter for electric vehicles. This converter has the following unique features over current options: bidirectional operation, higher efficiency over entire charging period, less number of components, and an air-cooled thermal management system. These features provide the advantages of enhanced efficacy, greater power density, and considerable cost savings, in comparison to the competing conventional method of utilizing an individual charger and an individual auxiliary load converter in the current market space.
This project addresses the following technology gaps as it translates from research discovery toward commercial application: (1) theoretical advancements in the design and development of ultra-compact, integrated vehicle-to-grid (V2G) and grid-to-vehicle (G2V) chargers and converters; (2) innovative thermal management methods for wide band-gap Silicon Carbide (SiC) based power electronic converters; (3) demonstration of a functional prototype integrated charger/converter for plug-in electric vehicles, (4) evaluation and prototyping a commercially valuable solution of proposed converter against conventional technologies, and (5) developing a strategy for commercialization beyond this project. In addition, personnel involved in this project, PIs, undergraduates and graduates will receive innovation and technology translation experiences through technical and commercialization tasks. This will be achieved through design and packaging activities from the feasibility to prototyping stage.
The project engages researchers from University of Maryland and Genovation Cars Inc. to design, develop, and validate a prototype of this technology translation effort from research discovery toward commercial reality.
This is a one-year, $200K project.
CAREER: Deciphering Brain Function Through Dynamic Sparse Signal Processing
The ability to adapt to changes in the environment and to optimize performance against undesirable stimuli is among the hallmarks of the brain function. Capturing the adaptivity and robustness of brain function in real-time is crucial not only for deciphering its underlying mechanisms, but also for designing neural prostheses and brain-computer interface devices with adaptive and robust performance. Thanks to the advances in neural data acquisition technology, the process of data collection has been substantially facilitated, resulting in abundant pools of high-dimensional, dynamic, and complex data under various modalities and conditions from the nervous systems of animals and humans. The current modeling paradigm and estimation algorithms, however, face challenges in processing these data due to their ever-growing dimensions. This research addresses these challenges by providing a unified framework to efficiently utilize the abundant pools of data in order to deliver game-changing applications in systems neuroscience.
Converging lines of evidence in theoretical and experimental neuroscience suggest that brain activity is a distributed high-dimensional spatiotemporal process emerging from sparse dynamic structures. From a computational perspective sparsity is a key ingredient in rejecting interfering signals and achieving robustness in neural computation and information representation in the brain. The main objective therefore is to develop a mathematically principled methodology that captures the dynamicity and sparsity of neural data in a scalable fashion with high accuracy. By focusing on the auditory system as a quintessential instance of sophisticated brain function, this research investigates several fundamental questions in systems neuroscience such as plasticity, attention, and stimulus decoding. The research is integrated with education and outreach activities including high school level hands-on workshops, undergraduate capstone projects, and interdisciplinary course development.
This is a five-year, $180K grant. View the NSF award page here.
ONR: Human-Robot Collaborative Autonomy: From Multi-sensory Perception to Cognition and Execution
CAREER: Smart Sampling and Correlation-Driven Inference for High Dimensional Signals
Technological advances have driven modern sensing systems towards generating massive amounts of data, making it increasingly challenging to store, transmit and process such data in a cost effective and reliable manner. However, the ultimate goal in many information-processing tasks is to infer some parameters of interest, that govern the statistical and physical model of the data. This includes applications ranging from source localization in radar and imaging systems to inferring latent variables in machine learning. The number of parameters in such problems is much smaller than the acquired volume of data, which leads to the possibility of more intelligent ways of sensing high dimensional signals, that can exploit the statistical model of the signal (with or without invoking sparsity), and the physics of the problem. The objective of this project is to develop a systematic theory of smart sampling and information retrieval algorithms for modern sensing systems that exploit the correlation structure of high dimensional signals to significantly reduce the number of measurements needed for inference. The proposed research can lead to deployment of fewer sensors (than what is traditionally required), as well as more energy efficient ways to collect and process spatio-temporal data that will positively impact a number of applications across disciplines, such as, high resolution imaging, remote sensing, neural signal processing and wireless communication. The educational component of this project aims at integrating the research outcomes into innovative teaching platforms such as ''Sense Smarter'', and ''Signals Everywhere'' that will help train the next generation of electrical engineers, and encourage them to pursue careers in STEM fields.
The technical component of the project has three interconnected goals: (i) designing fundamentally new geometries for correlation-aware samplers that exploit the statistical as well as physical signal models, (ii) developing, and analyzing the performance of new correlation driven algorithms to understand fundamental capabilities of correlation-aware samplers, and (iii) exploiting the ideas behind correlation-aware samplers to develop more efficient algorithms for solving bi- and multi-linear problems. Design of these samplers will provide new theoretical insights into properties of quadratic samplers, and will help address fundamental mathematical questions that can be of independent interest. The samplers also facilitate the development of new inference strategies, and the proposed rigorous theoretical analysis of these algorithms is expected to fundamentally advance our current understanding of the limits of parameter estimation from compressed data. Finally, the ideas behind correlation-aware samplers have strong connections with problems in machine learning such as dictionary learning, and latent variable analysis, and they will foster future research advances in these areas.
This is a five-year, $500K award. View the NSF award page here.
NIH NIDCD: Auditory Scene Analysis and Temporal Cortical Computations
Simon will use magnetoencephalography (MEG) to record from the auditory cortexes of the brains of human subjects, specifically the temporally dynamic neural responses to individual sound elements and their mixtures. Linking the neural responses with their auditory stimuli and attentional state will allow inferences of neural representations of these sounds. These neural representations are temporal: neural processing unfolds in time in response to ongoing acoustic dynamics. Simon will determine how the auditory cortex neurally represents speech in difficult listening situations.
This is a National Institutes of Health National Institute on Deafness and Other Communication Disorders R01 grant, "Auditory Scene Analysis and Temporal Cortical Computations." The five year, $1.5M grant started March 1, 2015. The research will further the understanding of how in an environment with many sounds and voices, people are able to concentrate on an individual voice and what it is saying.
AFOSR: Air Force Center of Excellence on Nature-Inspired Flight Technologies and Ideas (NIFTI)
The Air Force Center of Excellence on Nature-Inspired Flight Technologies and Ideas (NIFTI) will conduct research into how animals move, navigate and use their senses, and create solutions for challenging engineering and technological problems related to building small, remotely operated aircraft. It is housed at the Univerity of Washington, and in addition to Maryland researchers, includes faculty from Case Western Reserve University and international partners like Imperial College, University of Bristol, University of Sussex and Oxford University in the U.K. and Lund University in Sweden.
The NIFTI center, one of six AFOSR COEs nationwide, is funded by the U.S. Air Force for up to $9 million over six years. It will focus on three main research areas:
Locating objects. Researchers will look at how animals are able to find prey, a mate or food sources by encoding and processing information through their senses.
Navigating in complex environments. Insects and bats often fly in windy and crowded spaces, skillfully avoiding collisions. Scientists will study how their neurological and physiological systems function to allow them to move in these ways.
Navigating in sensory-deprived environments. Animals often fly in low light or nearly complete darkness, and in places where their ability to smell and hear might be compromised. Researchers will look more broadly at how animals use sensory information and how they make decisions about flight under different contexts.
Learning from the behavior of insects and animals could inspire more advanced micro-air vehicles, or small, flying robots. These could be used in difficult search-and-rescue missions, to help detect explosives or mines when it would be too dangerous for humans to go on foot or in vehicles, and for environmental monitoring.
NSF CPS: MONA LISA—Monitoring and Assisting with Actions
UMIACS Associate Research Scientist Cornelia Fermüller is the principal investigator and Professor John Baras (ECE/ISR) and ISR-affiliated Professor Yiannis Aloimonos(CS/UMIACS) are the co-PIs on a three-year, $800K NSF Cyber-Physical Systems grant, “MONA LISA - Monitoring and Assisting with Actions.” The research is being conducted in the Autonomy Robotics Cognition (ARC) Laboratory.
Cyber-physical systems of the near future will collaborate with humans. Such cognitive systems will need to understand what the humans are doing, interpret human action in real-time and predict humans' immediate intention in complex, noisy and cluttered environments.
This research will develop a new three-layer architecture, motivated by biological perception and control, for cognitive cyber-physical systems that can understand complex human activities, focusing specifically on manipulation activities.
AFOSR: Simulation-Based and Risk-Sensitive Methodologies for Stochastic Optimization and Control
This research will study basic questions aimed at challenges in information superiority, logistics, and planning. The researchers will develop and analyze new algorithms for the simulation optimization approach of sequential response surface methodology by incorporating direct gradient estimates; develop and analyze new global stochastic kriging simulation metamodels using an extrapolation method enabled by direct gradient estimates; utilize risk-sensitive cost functions to achieve express risk preferences and robustness in control problems; study how incorporation of risk-sensitivity affects the behavior of decision makers and controllers; develop and study efficient sampling and simulation-based methods for risk-sensitive control problems; study population-based methods for finding and improving on a good set of policies in risk-sensitive problems; and apply these optimization methodologies to practical problems, such as preventive maintenance, path planning for unmanned aerial vehicles, data mining, supply chain management, and financial engineering
This is a three-year, $554K grant.
ONR: Bio-inspired Underwater Sensing and Control with Mechanosensitive Hairs
Associate Professor Derek Paley (AE/ISR) is the principal investigator for a three-year, $700K Office of Naval Research grant, “Bio-inspired Underwater Sensing and Control with Mechanosensitive Hairs.” Co-PIs on the grant are alumnus Xiaobo Tan, (EE Ph.D. 2002), an associate professor at Michigan State University; and Matt McHenry, an associate professor at the University of California, Irvine.
The researchers will develop an underwater robotic perception and control system based on the lateral line and vestibular systems in fish that will support a closed-loop control system using bio-inspired, multi-modal sensing. Emerging tools such as functional imaging (a technique used in parallel with optogenetics) will be used to help resolve the role of multi-modal sensing in behavior. Tools from comparative physiology, material science, and dynamical control systems will be applied to solve the problem of closed-loop sensing and robotic control with artificial lateral line and vestibular organs.
MURI: Evolutionary Mechanics of Impulsive Biological Systems: Guiding Scalable Synthetic Design
This five-year project falls under MURI Topic 1: Emulating the Principles of Impulsive Biological Force. In addition to the University of Maryland, other universities include Duke (lead institution), Stanford, Harvard, UMass Amherst and UC Irvine.
NSF CIF: Secure and Private Function Computation by Interactive Communication
This research takes an information theoretic approach to develop principles that govern secure or private function computation by multiple terminals that host user data. The goal of the terminals is to compute locally and reliably, a given function of all the possibly correlated user data, using an interactive communication protocol. The protocol is required to satisfy separate security and privacy conditions. The former stipulates for each terminal that a coalition of the remaining terminals should glean no more information about the data at the terminal from their own data and the communication -- than can be obtained from the function value. The latter protects each individual user's data at a terminal from a similar coalition. A common framework is developed for analyzing the distinct concepts of security and privacy, and new information theoretic formulations and approaches are proposed with the objective of understanding basic underlying principles. Potential applications arise, for instance, in: hospital databases that store clinical drug trial results or university databases with student performance records; private information retrieval from user data stored in private clouds; and security and privacy certifications for the identities/locations of communities and individuals participating in crowd-sourced traffic and navigation services.
MURI: Understanding and Controlling the Coupled Electrical, Chemical & Mechanical Excitable Networks of Living Systems
This five-year project, led by the University of Maryland, falls under MURI Topic 9: Exploiting Biological Electromechanics: Using Electromagnetics Energy to Control Biological Systems. Other universities participating in this MURI include Arizona State University, Johns Hopkins and UC-Davis.
ARO: Noncommutative Probability and Information Theories for Inference from Networked Multi-sensor Data
ARL: Physical Layer Security for Wireless Communications
NSF CIF: Efficient Codes and their Performance Limits for Distributed Storage Systems
The three-year, $300K “Efficient Codes and their Performance Limits for Distributed Storage Systems” grant addresses the efficient means of storing the huge amount of data being generated and collected. This research will develop more efficient data management procedures for large-scale distributed storage systems.
Large data centers and distributed storage systems have become more widespread, playing an ever-increasing role in everyday computational tasks. While a data center should never lose data, industry statistics confirm that disk failures occur on a daily basis. Barg will develop methods and ideas about error correcting codes that will enable systems to provide better guarantees against data loss and reduce the amount of data that needs to be moved to enable recovery of information lost due to disk failures.
NSF Collaboative Research: Synergistic Exploitation of Network Dynamics and Knowledge Heterogeneity in Wireless Networks
“Synergistic Exploitation of Network Dynamics and Knowledge Heterogeneity in Wireless Networks” is a two-year, $120K award.
The continued growth of wireless networks and the services they provide is critically dependent on the availability and efficient use of wireless spectrum. This increasing demand is already pushing current commercial wireless networks to their limits and accentuating the need for transformative approaches for wireless system design. In response, engineers have been rapidly evolving these systems towards a dense, user-deployed, heterogeneous infrastructure characterized by aggressive reuse of spectrum. While these evolutionary architectures can realize high data rates, they operate in the presence of severe interference, a condition engineers traditionally try to suppress or mitigate.
Sennur Ulukus will work to exploit interference as side information. She will develop new approaches that embrace interference through synergistic exploitation of feedback, network dynamics and network knowledge heterogeneity
NSF CAREER: Decentralization and Parsimony for Implementable Control of Massively Interconnected Systems
Assistant Professor Michael Rotkowitz (ECE/ISR) is the recipient of a 2014 National Science Foundation Faculty Early Career Development (CAREER) Award for "Decentralization and Parsimony for Implementable Control of Massively Interconnected Systems." The five-year award is worth $400,000.
The advent of complex interconnected systems has created a need to design and analyze controllers that can observe information from only a small portion of a network but may ultimately affect a large portion of the network. This includes smart building management, multi-vehicle systems and convoys, irrigation networks, large array telescopes, and the power distribution grid. Developing these kinds of controllers is a key challenge in many cyber-physical systems problems. There is currently an enormous disconnect in decentralized control between celebrated theoretical advances and the concepts that are used for implementation, or even for computation. Rotkowitz’s research will produce a novel synthesis of the theory and methods of parsimonious recovery, which has undergone dramatic recent developments, with both the classical results and modern advances in decentralized control. It will further broaden the applicability of elegant and useful aspects of optimization theory to classes of problems that are paramount for the main scope of the project. The fundamental advances pursued in optimization and estimation have the potential to be of use much more broadly and to impact many other fields. This project further seeks to make broad impacts outside of its primary domain through collaborations with industry and with experimentalists, and through the creation of software tools for widespread use by non-experts.
NSF: A New Approach to Nonconvex Risk-Sensitive Stochastic Optimization
A New Approach to Nonconvex Risk-Sensitive Stochastic Optimization is a three-year, $340K grant that will fund development of a new framework for incorporating risk into sequential decision making under uncertainty. The two pillars of the approach are cumulative prospect theory and dynamic risk measures. The framework builds on both of these research streams to formulate a single theory that integrates subjective preferences in human behavior with normative decision-making objectives. Existing utility-based dynamic models cannot handle the nonconvexity implied by the behavioral models of prospect theory, whereas the framework allows the probability weighting found in cumulative prospect theory to be combined with the usual outcome weighting of traditional expected utility formulations in a sequential decision-making model that incorporates both types of risk sensitivity. The framework will be used to develop efficient dynamic programming sampling and simulation-based methods for risk-sensitive optimization and control problems, and to investigate how the new modeling of risk-sensitivity affects the behavior of decision makers.
The research will provide an alternative framework for decision making under risk to currently existing approaches. The framework unifies the predominantly descriptive research stream of prospect theory coming primarily from psychology and behavioral economics with the normative approaches generally associated with the microeconomics and operations research communities. From this new approach arise a host of challenges, both theoretical and computational. Algorithms will be developed that can be used to address practical operational and tactical decision-making problems arising in a wide variety of application areas, from manufacturing and supply chain management to service systems, including health care, transportation, and financial engineering.
NIH BRAIN Initiative: new imaging technologies and data analysis techniques
This is a three-year, $1.7 million grant from the National Institutes of Health (NIH) to develop new imaging technologies and data analysis techniques that will further understanding of how large networks of neurons in the brain interact to process sensory information. This knowledge will help researchers identify the precise interactions between millions of nerve cells that drive behavior, like decision-making and speaking, and alterations in these interactions that may be responsible for disorders such as schizophrenia, autism and epilepsy.
The grant is one of the first awarded by the Brain Research through Advancing Innovative Neurotechnologies (BRAIN) initiative, (link is external) part of President Obama’s focus aimed at revolutionizing the understanding of the human brain. The BRAIN Initiative is jointly led by the NIH, Defense Advanced Research Projects Agency of the U.S. Department of Defense, National Science Foundation, and Food and Drug Administration.
Maryland Innovation Initiative: Integrated Power Electronic Charger/Converter for Electric Vehicles
In this work, Khaligh will develop an integrated and highly efficient power electronics interface for electric vehicles. The total amount of funding is $100,000. Maryland Innovation Initiative This is a Phase I Research and Development grant, “Integrated Power Electronic Charger/Converter for Electric Vehicles.”
Optimizing Sensor Arrays for Waveform Enhancement
This six-month, $50K NSF I-Corps grant, Optimizing Sensor Arrays for Waveform Enhancement, will build a system consisting of an optimized large scale microphone array that allows spatial audio selection. This system can focus in on a target source while suppressing interferences from a wide variety of locations. In other words, the proposed system allows users to listen in on selected target source even though the source may be surrounded by a host of other interfering sources. The proposed technology achieves significant gains over current microphone array implementations through joint optimization of microphone placement and design.
The proposed technology can process acoustic and electromagnetic waveforms to discover both the number and location of sources in multi-path, noisy environments. The technology separates each source by either cancelling or attenuating interferences and identifies previously recognized sources. Additionally the technology works in environments where sources both move and outnumber the number of sensors. The technology optimizes sensor placement and processing using state of the art optimization and statistical modeling techniques.
DOE: NEES EFRC renewed for four years
The U.S. Department of Energy’s (DOE) Basic Energy Sciences has renewed its support for the University of Maryland’s (UMD) Nanostructures for Electrical Energy Storage Energy Frontier Research Center (NEES EFRC) for another four years. The renewal is based both on the NEES EFRC’s achievements to date and the quality of its proposals for future research.
NSF CMMI: New Approaches for Simulation-Based Optimal Decision Making
Simulation is widely used in many industrial settings, from manufacturing and supply chain management to service systems, including health care, transportation, and financial services. Due to the complexity of many of these systems, however, computation has often been a limiting factor in solving large-scale problems based on simulation models, even with the continuing advances in computing power. This award supports fundamental research leading to new algorithms that would improve the efficiency of finding optimal decisions for many problems in the manufacturing and service industries mentioned above, and thus lead to direct benefits to the U.S. economy and society. The research involves mathematical models, computing, applied probability, and statistics. This is a three-year, $220K grant. Read more
NIH NIDCD: Spectro-Temporal Plasticity in Primary Auditory Cortex
Auditory experience can reshape cortical maps and transform receptive field properties of neurons in the auditory cortex. The exact form of this plasticity depends on the behavioral context, and the spectrotemporal features of the salient acoustic stimuli. Neuroscientists believe that auditory cortical cells may undergo rapid, context-dependent changes of their receptive field properties when different auditory behavioral tasks are undertaken. This kind of plasticity would likely involve a selective functional reshaping of the underlying cortical circuitry to sculpt the most effective receptive field for accomplishing the current auditory task.
Shamma and his research team will explore the underlying mechanisms that give rise to this extraordinary functional plasticity. They will extend studies of task-related plasticity in the auditory cortex to a variety of new tasks involving speech stimuli, new behavioral paradigms (contrasting discrimination versus recognition). They will explore plasticity in higher-order auditory cortical fields, and investigate the possible role of top-down signals from frontal cortex in modulating adaptive plasticity in the auditory cortex.
This is a one-year, $320K grant.
NSF CMMI: Motion Guidance for Ocean Sampling by Underwater Vehicles using Autonomous Control and Oceanographic Models with Forecast Uncertainty
This project addresses fundamental questions on how to select the optimal locations to collect observations and how to ensure that the sensor platforms travel to these locations along informative paths in an expansive, dynamic process such as the ocean. The significance of the proposed research lies in the observation that climate processes occur on long time scales. Understanding these processes requires a combination of ocean models and observations, which can be collected over large space-time volumes by fleets of high-endurance autonomous submarines that steer intelligently to maximize the utility of their measurements. Underwater vehicles that sample the ocean interior are important for understanding ocean processes in general, because -- unlike weather prediction in the atmosphere -- the subsurface ocean environment is difficult to sample remotely. Thus, the long-term goal of this project is create new path-planning strategies for unmanned, mobile sensor platforms to measure information-rich but undersampled dynamic processes in the ocean. Indeed the methods developed in this project will be readily transferrable to operational data assimilation systems.
The specific objective of the research is to apply tools from data assimilation, nonlinear control, and dynamical systems theory to design sampling trajectories for accurate estimation and prediction of circulating ocean currents represented by a system of vortices. This is a three-year, $504K grant. Read more.
UMD Research and Innovation Seed Grant: Temporal Auditory Coding in Schizophrenia and Treatment-Resistant Auditory Hallucination
Simon and Hong will investigate the neural processing of rhythmic sounds (whether speech or simpler sound rhythms) in schizophrenia patients with treatment-resistant auditory hallucinations, compared to neural processing in patients whose auditory hallucinations are treatable, and with healthy listeners. The neural mechanisms underlying these diverse abnormalities, which are measured by electroencephalography and magnetoencephalography techniques, are not known. This research will advance the state of research in schizophrenia.
Hong is Chief of the Neuroimaging Research Program in the Department of Psychiatry and the director of the UM Center for Brain Imaging Research.
NSF CMMI: Graded-Index Metamaterial Waveguides: An Innovative Approach to Acoustic Wave Control
Acoustic waves play an important role in many applications, such as homeland security (e.g. sonar systems), healthcare (e.g. ultrasound imaging), and industry (e.g., non-destructive damage detections). However, there are currently limited functional acoustic materials that can effectively control and manipulate acoustic waves and be employed for next-generation acoustic-based devices. This award supports fundamental research on guiding, compression, amplification, and localization of acoustic waves through novel artificial acoustic materials (i.e., acoustic metamaterials). These engineered materials possess unique properties that are unachievable in natural materials. This work will open up new avenues towards the development of novel functional acoustic devices, which can potentially overcome the fundamental limitations encountered in conventional acoustic technologies. Various disciplines including physics, material science, medicine, measurement science, and energy sciences will benefit from different facets of this research. This award will also help broaden the participation of underrepresented groups in research and enrich the learning experience of students with innovative projects in an interdisciplinary curriculum integrated with the research findings.
Through combined analytical, numerical, and experimental studies, the goal of this work is to achieve a fundamental understanding of the acoustic wave propagation and guiding mechanisms, material dispersion, effective refractive indices in various graded-index metamaterial waveguides. The largely unexplored properties of these acoustic metamaterials, including the remarkable wave compression and field amplification properties, will be investigated. This research will enrich the knowledge in the growing field of anisotropic metamaterials and lead to new methodologies for control and manipulation of acoustic fields with metamaterials.
Graded-Index Metamaterial Waveguides: An Innovative Approach to Acoustic Wave Control is a three-year, $330K grant.
NSF Collaborative Research: Observing, Analyzing and Modeling Design-Team Problem-Decompositions in Facility Design
Engineers work in teams to solve complex system design problems like determining the layout of a factory or medical facility. Many problems are too complex to be solved all at once, so engineers separate the problem into a set of subproblems and solve the smaller subproblems. Because this decomposition strategy affects the overall quality of the facility design, it is important that the teams use good decomposition strategies.
Herrmann will conduct fundamental research into how teams of engineers solve medical and factory facility design problems— an important class of system design problems—and how their strategies affect the performance of the facilities they design. The medical facilities being designed are points of dispensing medication to the public in a public health emergency.
The research team will identify the reasoning processes and problem decompositions used by design teams to solve facility design problems and generate hypotheses about which decompositions lead to better solutions. This in turn will enable future research on how to design better design processes.
This is a two-year, $150K NSF Collaborative Research grant.
NSF Collaborative Research: RIPS Type 2: Quantifying Disaster Resilience of Critical Infrastructure-based Societal Systems with Emergent Behavior and Dynamic Interdependencies
This project will create a way to measure the resilience of critical infrastructure-based societal systems (CISSs) that are necessary for community functioning. A CISS is comprised of interdependent buildings that together serve a community function and that are dependent on networks of critical lifelines (water, wastewater, power, natural gas, communications and cyber-communications, and transportation). They are a family of structures that are linked by occupancy type, people, policies, information, geographic location, and/or building services, and thus also rely on human, organizational, political, and cyber links. Examples of a CISS structure include, but are not limited to, a school district, a healthcare delivery system, a government building, a university campus, a hospitality facility, a residential building, or a central business district. The project will focus on the impact of single or compound hazardous events on CISSs. The initial loss of a structure due to physical damage can spread throughout the CISS or its supporting lifelines. Subsequently, these interdependencies are dynamic and change over time through human intervention, emergent organizational behaviors, and policy changes. Finally, repairs and work-arounds can diminish the impact of the hazardous event(s). As a test, the resulting framework and specific techniques will be demonstrated on one type of CISS: a healthcare system. Insights gleaned from this test case can be applied to improve, build, and maintain communities that are more likely to withstand disruption or disaster. This effort will directly inform practicing healthcare managers and emergency planners.
The project will uniquely incorporate public policy, organizational policy, organizational behaviors and risk communication into a broader assessment of disaster resilience data of multiple hazards.
Collaborative Research: RIPS Type 2: Quantifying Disaster Resilience of Critical Infrastructure-based Societal Systems with Emergent Behavior and Dynamic Interdependencies is a three-year, $1.45M grant.
NIH NIDCR: Magnetic Delivery of Therapeutic Nanoparticles to the Dental Pulp
Pulpitis, is an inflammation of the dental pulp deep within the tooth, most often experienced as a sharp pain when eating ice cream or having a cold drink. Usually treatment involves the dreaded root canal procedure to remove the damaged pulp. Depireux and Masri’s research could give dental practitioners a much less invasive treatment option. The pair are developing a new, patent-pending technique to deliver medication directly into the center of a tooth.
The research uses strong magnetic fields to move medication-coated, magnetic nanoparticles through the tooth's dentin and into the pulp. Dentin, a solid substance that encases the pulp, is surrounded by a harder-than-bone layer of enamel. "When you have a cavity, usually the enamel has been damaged and the dentin is exposed, so when you eat or drink, it will stimulate the fluid within the dentinal tubules and cause pain," Masri explained.
The researchers are using tubules, the microscopic channels that travel through the dentin into the tooth pulp, as the vehicles to deliver the inflammation-reducing or antibiotic medication. They have designed a system of magnetic arrays effective for upper or lower teeth. By manipulating a series of cube-shaped magnets, they can control the magnetic field so the nanoparticles are pulled through the tubules into the tooth pulp. This is a two-year, $450,000 grant.
NSF: Optimal Distributed Estimation over Shared Networks
A class of collision channels to model the effect of simultaneous transmissions is considered. In this approach, the problem, from the point of view of each sensor, is recast as one of designing an optimal remote estimation system across a new class of erasure links, and in the presence of communication costs. A connection to optimal quantization theory will be investigated to obtain effective numerical optimization algorithms. The proposed approach also leads to a new class of optimal quantization problems for which the cost is non-uniform across representation symbols. We explore how the ideas above can be used to find the optimal solution to particular cases of the problem.
Optimal Distributed Estimation over Shared Networks is a three-year, $387K grant.
NSF Collaborative Research: Theoretical Foundation of Distributed Wireless Channel Access
Wireless networks tend to not be either energy or bandwidth efficient. This is due to a lack of fundamental understanding of how to share wireless media among spatially distributed users. Historically, wireless channel access research has followed either a traditional information-theoretic approach that assumes perfect user coordination and ignores the modularized network architecture, or a traditional network-theoretic approach that largely focuses on access control protocols and ignores the impact of the physical layer. Ephremides’ research will bridge the gap between these two approaches by developing a theoretical foundation for channel access in distributed wireless systems.
“Theoretical Foundation of Distributed Wireless Channel Access” is a three-year, $250K National Science Foundation Collaborative Research grant.
NSF Collaborative Research: Effects of production variability on the acoustic consequences of coordinated articulatory gestures
Point source tracking of the speech articulators will be collected concurrently with the corresponding acoustics. Speakers will record speech at both a normal and rapid pace (the purpose of the latter is to increase significantly the degree of variability in the signal). This data will allow for the investigation of whether speakers always move their speech articulators in the direction of a desired target (e.g. tongue tip to teeth in producing /t/) even when a rapid production pace occludes the relevant acoustic information (as in "perfect"). If confirmed, this finding will point the way towards making recognition systems more robust through the incorporation of articulatory information. In addition, such data will support the development of a speech inversion system capable of 'uncovering' hidden articulatory movements potentially masked from the acoustics.
Effects of production variability on the acoustic consequences of coordinated articulatory gestures is a two-year, $132K grant.
AFOSR MURI: Security Theory for Nano-Scale Devices
Researchers at the University of Connecticut, the University of Maryland, and Rice University have won a $7.5 million grant via an Air Force Office of Scientific Research (AFOSR) MURI to address the topic “Security Theory for Nano-Scale Devices.” Ten researchers across the three institutions will collaborate to analyze and upgrade security protections for nano-scale computer hardware. Their goal is to develop Universal Security Theory for the evaluation and design of nano-scale devices. Nano-scale devices, many thousands of times smaller than the width of a human hair, are increasingly implemented by the electronics industry to perform vital functions supporting national security, commerce, energy, and transportation. Nano-scale chips are used in a wide variety of applications from air traffic control computers to medical devices to personal cell phones and the nation’s electric grid and banking system. Maryland's contributions to the research will leverage their past work and expertise in hardware security, digital watermarking and fingerprinting for VLSI design, circuit and design obfuscation, design and implementation of physical unclonable functions, 3-D integrated circuit integration and manufacture-aware design.
NSF CPS Collaborative Research: Designing semi-autonomous networks of miniature robots for inspection of bridges and other large infrastructures
This new research will create a self-organizing network of small robots that could aid in visually inspecting bridges and other large civilian infrastructure. As they create the network, the researchers will establish new design and performance analysis principles and technologies.
The networked robots could remotely and routinely inspect complicated structures, like the assemblage of girders supporting a suspension bridge. The robots will use wireless information exchange to autonomously coordinate and cooperate in the inspection, and whenever possible, they will report back images and key measurements to experts for evaluation. The tiny networked robots will be able to access tight spaces, operate under various weather conditions, and autonomously execute tasks for long periods of time.
The researchers are collaborating with Resensys, a company that specializes in remote bridge monitoring. Resensys is a portfolio company of the Maryland Technology Enterprise Institute's (Mtech) Technology Advancement Program, an Mtech VentureAccelerator graduate and a former UMD $75K Business Plan Competition winner. Resensys’ President and CTO Mehdi Kalantari (EE Ph.D. 2005) is an assistant research scientist in the Electrical and Computer Engineering Department.
"Designing semi-autonomous networks of miniature robots for inspection of bridges and other large infrastructures" is a three-year, $850K grant, part of NSF's National Robotics Initiative.
NSF: Phaseless Reconstruction and Geometric Analysis of Frames
The research studies two problems, each exploiting redundancy of representations in mathematics and engineering, and develops new methods to recover a signal from a nonlinear processing scheme. The first problem is related to signal reconstruction from magnitudes of a redundant linear representation (the so-called phase retrieval problem). The second problem involves a geometric analysis of frames and connections to deep problems in mathematics (such as the Kadison-Singer problem). This analysis leads to faster methods that offer better quality and resolution of the reconstructed signals in applications from X-ray crystallography, data communication on fiber optics, and speech processing. Undergraduate and graduate students involved in this project are trained for a globally competitive STEM workforce by learning to develop new mathematical tools to solve real-world problems.
Phaseless Reconstruction and Geometric Analysis of Frames is a three-year, $106K grant.
DoD: Shared Perception, Cognition and Reasoning for Autonomy
NSF CPS Breakthrough: Compositional Modeling of Cyber-Physical Systems
Compositional Modeling of Cyber-Physical Systems is a three-year, $500K grant to develop new mathematical modeling techniques for cyber-physical systems. Cleaveland and Marcus will devise novel conceptual methods for assembling systems from subsystems, and for reasoning about the behavior of systems in terms of the behavior of their computational or physical subsystems. The research will enable scientists and engineers to develop more realistic models of the systems they are designing, and to obtain greater insights into the eventual behavior of these systems without having to build costly prototypes.
Specifically, the researchers will develop the novel modeling paradigm Generalized Synchronization Trees (GSTs) into a rich framework for both describing cyber-physical systems (CPSs) and studying their behavior under interconnection. GSTs are inspired by Milner's use of Synchronization Trees (STs) to model interconnected computing processes, but GSTs generalize the mathematical structure of their forebears in such a way as to encompass systems with discrete ("Cyber") as well as continuous ("Physical") dynamics.
NSF: Time-scale analysis for the synthesis of thin-film deposition reaction kinetics models
This project will investigate the mathematical structure of differential-algebraic (DAE) systems of equations describing surface reaction species during ALD and CVED thin film deposition processes. A reaction network factorization procedure will be developed that partitions surface reaction and deposition species dynamic balances into sets of relatively slow (deposition), fast (equilibrium), and instantaneous (conserved) modes. The project will determine conditions under which the factorization works, the importance of fixed points of the equations, and reaction fluxes of chemical species.
Time-scale analysis for the synthesis of thin-film deposition reaction kinetics models is a three-year, $300K grant.
NSF CIF: Foundations of Energy Harvesting Wireless Communications
Foundations of Energy Harvesting Wireless Communications is a three-year, $250K, NSF Communication and Information Foundations grant. Continuing her work on devices that operate with energy harvested from the environment, Sennur Ulukus will establish fundamental performance limits and design principles for wireless communication networks containing them.
Ulukus identifies the randomness, intermittency, and causality of energy availability, and the uncertainty about the energy states of the transmitters at the receivers, as new ingredients to be incorporated in determining the fundamental performance limits of energy harvesting wireless communication systems. She will determine the information theoretic capacity of an energy harvesting link and the accompanying optimum coding and transmission scheme by incorporating energy harvesting constraints into the information theoretic capacity formulation.
NSF BRAIN EAGER: Wireless Measurement of Neuronal Currents Using Spin-Torque Nano-Oscillators
The brain is a complex network of interconnected circuits that exchange signals in the form of “action potentials,” which hold the key to understanding cognition and complex thought. Currently available non-invasive methods for probing neuronal activity are limited because they cannot achieve sufficient spatial or temporal resolution to observe individual action potentials from single neurons or small clusters.
Waks and Shapiro will develop a novel approach for non-invasive measurements that can read out individual action potentials across the entire brain. Their project will take advantage of recent advances in spintronic devices to create injectable nano-reporters. These nano-reporters will detect weak electrical signals in the brain and convert them to microwave signals that can be detected wirelessly outside the body using a spin-torque nano-oscillator (STNO). This approach could ultimately lead to the first non-invasive technology capable of measuring activations of individual neurons and small-scale neuronal networks in primates and humans, and could have a major impact on the understanding of the inner workings of the brain and cognition. The approach also could have important clinical applications, particularly in neurological disorders and brain machine interfaces.
This two-year, $300K award is made jointly by two NSF programs: the Instrument Development for Biological Research program (IDBR) and Emerging Frontiers (EF) in the Directorate of Biological Sciences (BIO).
Sampling Rate Distortion
The three-year, 500K NSF Communication and Information Theory grant will fund research that takes an information theoretic approach to understanding principles that govern a coordinated rate-efficient sampling of multiple signals and centralized compression of the sampled subset. The goal is to reconstruct the entirety of the signals within acceptable distortion levels. The research has three main components: an integrated analysis of sampling and rate distortion behavior, and their tradeoffs; sampling rate distortion theory for Markov random fields; and sampling rate distortion performance for signals with memory. Expected outcomes are a characterization of fundamental performance limits of optimum sampling rate and lossy compression rate and their interplay, together with the best choice of sampling mechanisms and attendant processing for reconstruction.
The investigators' technical approach involves the development of a principle of "sampling rate distortion" which lies at the intersection of specialities in information theory and signal processing, and has the larger objective of elucidating material connections between sampling and rate distortion performance. The performance of specific sampling and rate distortion processing schemes will be investigated. Specific groups of open problems chosen for investigation address a general class of multisignal models for sampling and lossy data compression. These are motivated by potential applications including dynamic thermal management for on-chip temperature control during runtime; network function computation; and image restoration, surface reconstruction and visual integration in computer vision.
The Role of Surface-Energy on Texture Development in Rare-Earth-Free Auxetic and Magnetostrictive Materials
This three-year, $454K NSF Collaborative Research grant will fund research that will lead to the understanding needed to achieve the performance capabilities of costly single-crystal alloys in low-cost polycrystalline alloys. Models of atomic structure and energy-based models of crystal growth processes will be used to gain insights into how to control and target the selective growth of desired crystals at the expense of crystals with less favorable mechanical and/or magnetostrictive properties.
The iron-aluminum and iron-gallium alloys that are one focus of this project have been targeted because of preliminary results that suggest they are good candidates for a sustainable alternative to magnetostrictive alloys used in industrial and defense applications that contain rare-earth elements like Terbium and Dysprosium.
This research aligns well with the need for advances in the development of sustainable materials, as it focuses on methods for processing magnetostrictive alloys that allow earth-abundant, inexpensive and benign chemicals to be used as a replacement for expensive critical materials, the rare-earth elements that are both significantly more costly and significantly less abundant in the Earth's crust.
The iron-aluminum and iron-gallium alloys to be studied are highly-auxetic, a mechanical property that is generally found in polymers but rarely in metals. The potential for high industrial impact of a structural auxetic alloy exists, as studies of non-structural auxetics (i.e. polymers) indicate that auxeticity can be used to enhance resistance to fracture and indentation.
Presidential Early Career Award for Science and Engineering (PECASE)
Paley, whose PECASE nomination was sponsored by the Department of Defense, is the founding director of the Collective Dynamics and Control Laboratory and a member of the Alfred Gessow Rotorcraft Center, the Maryland Robotics Center, the Program in Neuroscience and Cognitive Science, and the Applied Mathematics and Statistics, and Scientific Computation Program.
The Sleep Environment as a Risk Factor for Eye Pressure Elevation
A two-year, $180K NSF EAGER grant, The Sleep Environment as a Risk Factor for Eye Pressure Elevation, will obtain the preliminary data needed to establish that a correlation exists between the physical environment in contact with eyes during non-supine sleep and sustained periods of elevated intraocular pressure (IOP) during non-supine sleep. The hypothesis to be tested by this research is that a traditional sleep environment, i.e. resting on a conventional mattress and pillow, places the eyes of non-supine sleepers in a physical environment that leads to an elevation in IOP. To test this hypothesis, study subjects, half with healthy eyes and half with asymmetric glaucoma damage, will be fitted with two Sensimed Triggerfish® wireless, contact-lens-based strain sensors (one in each eye). These sensors will be used to record changes in IOP throughout the night. The studies will be conducted at the Johns Hopkins Sleep Center to simultaneously record video of sleep positions. IOP and position data will be used to correlate eye contact with the physical environment to changes in IOP as well as to establish potential differences in the sensitivity of subjects with and without glaucoma to variations in physical environment properties.
The researcher hopes to advance the understanding of a here-to-fore overlooked factor that contributes to the elevation of IOP. The significance of is that IOP elevation is primary risk factor associated with eye damage and vision loss in individuals with glaucoma. (Glaucoma is the second leading cause of blindness worldwide and affects an estimated 60 million people globally at this time; a number is expected to increase to 80 million by 2020) Understanding that the sleep environment contributes to the primary risk factor for disease progression will lead to developing strategies to fix or alter the environment.
The ability to obtain preliminary result to address this research is greatly facilitated by of the advent in 2011 of Sensimed's Triggerfish® wireless contact-lens-based strain sensors.
If the research hypothesis is demonstrated to be correct, the broader impact of the research on those with glaucoma-related visual impairment will be transformational. The impact on altering conventional wisdom, which completely neglects sleep environment as a risk factor for those with glaucoma, will be immediate. Further research will be necessary to address how to most effectively alter sleep environments to mitigate IOP elevation. The research will provide the preliminary results needed to raise awareness of that sleep environment can pose a significant risk for glaucoma patients who are non-supine sleepers, and that modifications to a sleep environment can be used to slow the progressive loss to field of vision experienced by these individuals.
Presidential Early Career Award for Science and Engineering (PECASE)
Bergbrieter's PECASE nomination was sponsored by the National Science Foundation.
Compliant Multifunctional Robotic Structures for Safety and Communication by Touch
Research enabled by the three-year, $600K Compliant Multifunctional Robotic Structures for Safety and Communication by Touch grant will enable better training of robots by enabling them to physically communicate via human touch using new compliant multifunctional structures. To achieve this, arrays of conducting polymers will be developed to form a system similar to the human nervous system that can sense shape and forces distributions. This sensor array will be integrated into composite foam structures using a scalable additive manufacturing process. To support development of models and to serve as proof-of-concept for these multifunctional structures on robotic platforms, simulated co-robotics experiments will be conducted using a robotic arm interacting with objects of varying compliance. Experimental details of the associated contact mechanics will be quantified in real-time using Digital Image Correlation and conventional video imaging. Output from the sensor array will then be related to shape and force distributions by solving the nonlinear inverse problem using a novel Singular Value Decomposition method. Research results will be documented and disseminated, and the experiments will be converted to STEM demonstrations targeted at educating young girls.
This research will lead to new compliant, scalable, sensing structures that simultaneously monitor in real-time both global and local shapes, as well as force distributions. Since compliant multifunctional sensing structures do not yet exist for robots, it is envisioned that the proposed work will enable realization of new bio-inspired control principles for training robots. This will significantly advance the ability to make safer interactions and decisions in co-robotics by differentiating robotic interactions with humans from other objects in their environment. The proposed integration of research and education will train new mechanical engineers to create multifunctional products that enable new products and new capabilities in existing products in critical areas such as healthcare. The new fabrication methods will enable these structures to be manufactured in the United States in a cost-competitive manner, increasing employment.
MIPS: Power Conditioning System for Wind Harvesting
NSF: Incentive Compatible Wireless Security
Professor Sennur Ulukus (ECE/ISR) received a $400K wireless security grant from the National Science Foundation (NSF). The award is a joint 4-year grant between Ulukus and her two colleagues, Aylin Yener from Pennsylvania State University and Randall Berry from Northwestern University, totaling $1.2 million.
The research goal is to create a practical setup for wireless security by amalgamating information theory with the theory of incentives to provide secure wireless cyber access. The researchers will develop mechanisms to incentivize non-altruistic cognitive nodes to participate in information theoretic security protocols. They also will create incentive mechanisms for scenarios where all nodes have equal access to spectrum and need confidentiality, even from each other; techniques for providing security to groups of cooperative nodes and the associated trust issues; incentive mechanisms for combating active attacks; strategies for combating colluding adversaries; and mechanisms to ensure that nodes have the incentive to adopt a given security protocol.
NSF: Electrical-Thermal Co-Design of Microfluidically-Cooled 3D ICs
Associate Professor Ankur Srivastava (ECE/ISR) is the principal investigator of a new National Science Foundation Software and Hardware Foundation collaborative-research grant, Electrical-Thermal Co-Design of Microfluidically-Cooled 3D IC’s. The goal of the project is to develop and refine the micro-fluidic 3D IC cooling technology.
The three-year, $925K grant is a collaborative proposal between the University of Maryland (UMD) and the Georgia Institute of Technology (Georgia Tech). University of Maryland is the lead institution and Srivastava is the lead PI. The Georgia Tech investigators include Dr. Muhannad Bakir and Dr Yogi Joshi.
The project investigates the need for co-design of the electronic as well as the cooling side of computer systems, and more specifically 3D ICs. 3D ICs are touted as the next innovation in integration technology. Due to higher device densities, thermal issues in 3D ICs present a challenge which requires further research and exploration. This research explores interlayer micro-fluidic cooling technology for heat removal in 3D ICs. Micro-fluidic cooling enables one to control the level of cooling available in different areas of the chip. This provides new opportunities for co-design of the cooling as well as the electronic aspects of the system with respect to determining the level of computing and cooling in different areas of the chip. This co-design may significantly improve the performance and energy efficiency of the system.
NSF: CIF: Toward Trustworthy Information Forensics and Anti-Forensics
The path of technological evolution has naturally led to a critical issue to ensure content, devices, and intellectual property being used by authorized users for legitimate purposes, and to be able to forensically prove with high confidence when otherwise. When information goes through various devices and processing, there are inherent traces left from each processing step. These traces serve as intrinsic fingerprints and are essential for forensic analysis. This research involves developing a joint forensic and anti-forensic framework to leverage the universal intrinsic fingerprints to gather traces of evidence to answer who has done what, when, where, and how. The main thrusts of this research include:
(1) Investigation of the strategy space and adversarial dynamics on a broad range of forensic problems associated with content, device and emerging sensing paradigm;
(2) Development of a theoretical foundation to understand the fundamental performance limit and establish formal notions of forensicability in an information processing chain; and
(3) Development of an Information Forensic and Anti-Forensic Engine along with a benchmark set and an online portal for integrated research, education, and outreach.
This research establishes a comprehensive foundation for the field of trustworthy information forensics, with a broad range of important applications tackled from a new angle of thinking. The research program seamlessly integrates with the education and outreach program through the establishment of the Forensic Engine and the collaboration with law and policy professionals. Through establishing trust and provenance in digital domain, closely involving and training students, collaboration in the research community, and partnership with law professionals and industry, this research contributes to law enforcement and national security as well as promotes the emerging science of trustworthy forensics to a broad audience.
ARO MURI: Information Engines: Nanoscale Control, Computing and Communication out of Equilibrium
Professor P. S. Krishnaprasad (ECE/ISR) and Professor Christopher Jarzynski (Chem-Biochem/IPST) are part of a new Army Research Office Multi-University Research Initiative (MURI) grant, "Information Engines: Nanoscale Control, Computing and Communication out of Equilibrium." The five-year award was recently announced by the Department of Defense.
Drawing on four distinct perspectives--computational mechanics, nonequilibrium thermodynamics, control theory, and nanoscale experiments--this project will investigate fundamental principles and algorithms for the creation of synthetic nanosystems that are able to gather, store, and manipulate information while immersed in a thermally noisy environment. Such capabilities appear to be a basis for achieving directed nanoscale flows of matter and energy. The team's research is also expected to yield insights into bio-molecular complexes with similar functionality.
NSF EAGER: Integrated On-Board SiC-Based Level-3 Charging for Plug-In Electric Vehicles
Assistant Professor Alireza Khaligh (ECE/ISR) is the principal investigator for a new National Science Foundation EAGER grant, “Integrated On-Board SiC-Based Level-3 Charging for Plug-In Electric Vehicles.” The objective of this electric vehicle-related research is to investigate, design, and develop an integrated, on-board, silicon carbide-based, level-3 battery charger, compatible with level-1 and level-2 charging, using the propulsion machine and its inverter for the next generation of plug-in vehicles. Khaligh will conduct comprehensive propulsion motor and inverter analyses and propose a rectifier/charger topology to charge the battery. He will investigate the possibility of eliminating power factor correction inductors for both single-phase and three-phase charging by using propulsion machine windings, without producing torque. This fundamental research will achieve breakthroughs in control, modeling and design of power electronic interfaces for electric vehicles.
High Performance Electronics using Microfluidics
HFSP: Multimodal Sensing in the Natural Environment
Professor Cynthia Moss (Psychology/ISR) is the principal investigator leading an international research team on "Multimodal sensing in the natural environment," a three-year research grant from the Human Frontiers Science Program.
The project will advance critical new insights to how animals process, represent and use multimodal sensory information from the natural environment. This includes how they build cognitive maps of their natural environments to make decisions for goal-directed actions. Through integrated field and lab studies, computer modeling and biomimetic robotics, the project will contribute to a deeper understanding of multisensory integration, scene analysis, and spatial navigation in natural settings.
AFOSR: Optimized Routing of Intelligent, Mobile Sensors for Dynamic, Data-Driven Sampling
Associate Professor Derek Paley (AE/ISR) is the principal investigator for a three-year, $600K grant from the Air Force Office of Scientific Research. The grant is for "Optimized Routing of Intelligent, Mobile Sensors for Dynamic, Data-Driven Sampling."
The long-term goal of this project is to provide a control-theoretic framework to enable intelligent, mobile systems to optimally collect sensor-based observations that yield accurate estimates of unknown processes pertaining to Air Force research, including human/vehicle surveillance and airborne contaminant release. Paley will apply tools from aerospace engineering, specifically nonlinear estimation and control, to design coordinated sampling trajectories that yield the most informative measurements of estimated dynamical and stochastic systems.
DURIP - Upgrade of Measuring and Testing Equipment for the Development of Energy-Efficient Wireless Sensor Networks in Research and Education
NSF: Exploring Power Network Attributes for Information Forensics
The three-year, $360K NSF Secure and Trustworthy Cyberspace grant will fund Wu's investigation of the scientific and technological foundations of the time, location and integrity of sensor recordings by exploiting novel intrinsic fingerprints in the environment. For example, such fingerprints include the small, random-like fluctuations of the electricity frequency, known as the Electric Network Frequency (ENF). These environmental fingerprints reflect the attributes and conditions of the power grid and become naturally "embedded" into video, audio or other types of sensor signals at the time of recording. They carry time and location information and may facilitate integrity verification of the primary sensing data. Answering questions about the time, location, and integrity of sensor recordings will have important applications in crime solving, counter-terrorism, journalism, infrastructure monitoring, smart grid management, and other commercial operations.
Modeling and Control of Magnetic Chemotherapy
The three-year, $301K NSF Collaborative Research grant aims to improve the delivery of chemotherapy drugs to target tumors. With existing chemotherapy, it is estimated that less than 0.1 percent of administered drugs are taken up by the tumor, while the remaining 99.9 percent go to healthy tissue, where they can cause severe and life-threatening side-effects. In magnetic drug targeting, chemotherapy can be attached to biocompatible magnetic particles. This allows magnetic control of the drugs: magnets placed outside the patient can potentially be used to focus the therapy to tumors.
Doing so is difficult. The human body is complex and it is not yet understood how to actuate the magnets (when to turn them on and off) to best direct the drugs to the tumors. The goal of this project is to develop sophisticated and experimentally-validated tools to better understand how magnetized chemotherapy moves through the body, and based on these to develop methods to optimally actuate the magnets to better direct the chemotherapy to tumors.
The broader impact will be a suite of techniques to improve magnetic drug targeting - potentially moving it from a method that could only focus drugs to single shallow tumors, to one that could access deep tumors as well as small and poorly vascularized metastatic tumors spread throughout the body.
Advanced Silicon Carbide based Novel Hybrid Energy Storage System for Plug-In Electric Vehicles
The three-year, $438K National Science Foundation GOALI (Grant Opportunities for Academic Liaisons with Industry) award will provide funding to develop a novel hybrid energy storage system for electric vehicles. The new system will be composed of a high energy-density battery pack, an ultracapacitor pack and a DC/DC converter. This new lightweight system will weigh less than a conventional high power-density battery pack alone. At the same time it will offer an increased battery lifetime. The new system will be developed, implemented and validated on the powertrain of a new electric car.
Optimized Routing of Intelligent, Mobile Sensors for Dynamic, Data-Driven Sampling
The long-term goal of this three-year, $600K project is to provide a control-theoretic framework to enable intelligent, mobile systems to optimally collect sensor-based observations that yield accurate estimates of unknown processes pertaining to Air Force research, including human/vehicle surveillance and airborne contaminant release. Paley will apply tools from aerospace engineering, specifically nonlinear estimation and control, to design coordinated sampling trajectories that yield the most informative measurements of estimated dynamical and stochastic systems.
Tracking Control of Nonlinear Systems Under Sensing, Computational, and Communication Constraints
ISR-affiliated Assistant Professor Nikhil Chopra (ME) is the principal investigator of a three-year, $325K grant from the National Science Foundation for “Tracking Control of Nonlinear Systems Under Sensing, Computational, and Communication Constraints.” The grant is part of NSF’s Energy, Power and Adaptive Systems program. The research will investigate control algorithms for resource constrained trajectory tracking in nonlinear systems.
NSF Collaborative Research: Understanding Magnetostrictive Galfenol Physics for Micro- and Nano-Scale Devices
The research focuses on structured analytical and experimental analysis of magnetostriction in iron-gallium (Galfenol) thin films and nanowires to advance understanding of the magnetostrictive physics at this scale and to enable transformative new micro- and nano-scale device functionality. This alloy system has the distinct advantage of having high strains in response to magnetic fields (400ppm) while also exhibiting the mechanical ductility and strength of iron. The ability to electrodeposit this active material is possible due to preliminary work which overcame the difficulty of Ga oxidation in aqueous electrolytes, and which therefore enabled FeGa metallic alloys to be fabricated as thin films and nanowires.
Understanding Magnetostrictive Galfenol Physics for Micro- and Nano-Scale Devices is a three-year, $310K award.
Physical Testbed System for Synthesis of Collective Behavior from Fundamental Building Blocks
Professor P. S. Krishnaprasad (ECE/ISR) has been awarded a DURIP 2012 grant by the Air Force Office of Scientific Research to support his work on principles and algorithms that underlie purposeful collective behavior in natural and engineered systems. The $300K award will help establish a Physical Testbed System for Synthesis of Collective Behavior from Fundamental Building Blocks.
NSF GOALI: Physically Based Models of Atomic Layer Deposition for High-Throughput Reactor Design
With new energy, electronics, and consumer product applications, and the emergence of highthroughput reactor designs, Atomic Layer Deposition (ALD) is set to become a major thin-film manufacturing tool. Deposited using an alternating sequence of exposures to gas-phase precursors that would otherwise spontaneously react, ALD allows for the controlled deposition of a wide range of ultra-thin films at relatively low temperatures and potentially perfect conformality. Despite the upsurge in ALD process and equipment development, research on modeling deposition mechanisms and reaction kinetics in particular, continues to lag efforts devoted to new precursor chemistries and reactor designs. Because ALD is by its essential nature a completely dynamic process with no equivalent to steady-state deposition, the objective and primary intellectual merit of this research is to develop physically based models describing both ALD reaction rates and the changes occurring on the growth surface using transition-state (absolute rate) theory concepts.
Physically Based Models of Atomic Layer Deposition for High-Throughput Reactor Design is a three-year, $297K award.
Speech Processing Algorithms for Elderly Listeners with Hearing Loss
The ADVANCE Program for Inclusive Excellence’s 2012 Interdisciplinary and Engaged Research Seed Grants awarded Professor Carol Espy-Wilson (ECE/ISR) and Professor Sandra Gordon-Salant (Hearing and Speech Sciences, BSOS) a seed grant for “Speech Processing Algorithms for Elderly Listeners with Hearing Loss.”
Magnetic drug delivery to the inner ear
Associate Professor Benjamin Shapiro (BioE/ISR) and ISR Associate Research Scientist Didier Depireux have teamed up on several research grants related to delivering drug therapies to the inner ear. This is a new collaborative area for the two ISR researchers.
A $50K, one-year University of Maryland Vice President for Research Seed Grant, Magnetically Delivering Therapies to Inner Ear Diseases.
A $100K, 16-month Maryland Industrial Partnerships Program (MIPS) grant, Magnetic Therapy Injection to Treat Hearing Loss.
A $5K, four-month I Rutel (OUHSC) subaward, Magnetic Injector for Targeted Delivery of Therapeutics.
An $80K, one-year SZI-Clark Seed Funding grant to establish a collaboration with Dr. Diego Preciado of Childrens National Medical Center in Washington, D.C., Magnetic Delivery of Drugs to the Middle Ear without Ear Drum Puncture.
NSF CSR: Easy PRAM-Based High-Performance Parallel Programming with Immediate Concurrent Execution (ICE)
Parallel programming is in crisis: its difficulty dissuades all but the most determined (and deep-pocketed) software vendors, and speedups are often disappointing for all but regular programs. Merely augmenting the substantial knowledge-base of parallel computing with incremental ideas in algorithms, programming languages, compilers, hardware, power or applications, interesting as they may be, is unlikely to change this reality.
This project advances a powerful idea for drastically improving ease-of-programming within the context of a holistic many-core research architecture called XMT. Our contention is that without the co-design of language and architecture, one cannot conquer the twin challenges of easy programming and efficient parallelization of irregular programs. Therefore we are developing a new easy-to-program language called ICE as part of ecosystem consisting of XMT, the PRAM algorithmic model, and ICE, that together deliver on this twin goal. The XMT architecture, developed at UMD over the last decade, is capable of exploiting fine-grained parallelism in irregular programs. ICE is based on the successful PRAM algorithm model, which provides a rich theory for parallel programming, and has led to published parallel algorithms for hundreds of problems.
Easy PRAM-Based High-Performance Parallel Programming with Immediate Concurrent Execution (ICE) is a four-year, $485K award.
Insect and Robot Locomotion with Heavy Loads
The ADVANCE Program for Inclusive Excellence’s 2012 Interdisciplinary and Engaged Research Seed Grants awarded Assistant Professor Sarah Bergbreiter (ME/ISR), Professor Barbara Thorne and Associate Professor Jeffrey Shultz (both from Entomology, CMNS) a seed grant, “Insect and Robot Locomotion with Heavy Loads.”
NSF CIF: Random key predistribution in wireless sensor networks -- The impact of partial visibility
With wireless sensor networks deployed in hostile environments, there is a need for cryptographic protection to enable secure communications services. Unfortunately, many approaches developed for general networking environments do not take into account the unique features of such wireless networks. Starting with the original scheme of Eschenauer and Gligor, random key predistribution schemes have been proposed to address this challenge. Much of the work on these schemes has been carried out under the full visibility assumption whereby sensor nodes are all within communication range of each other. However, the question remains whether randomized key predistribution schemes can indeed deliver the needed security guarantees under wireless communication constraints. To explore how this partial visibility affects two basic issues, namely secure connectivity and resiliency, we study random graph models which are obtained by intersecting two random graphs, namely a communication graph (to model the communications constraints of the wireless medium) and a cryptographic graph (to capture the given predistribution scheme). Our goal is to better understand performance trade-offs and to develop guidelines for dimensioning available cryptographic, communication and computing resources.
Random key predistribution in wireless sensor networks -- The impact of partial visibility is a three-year, $413K award.
New Approaches and Technologies Underlying Mechanisms Associated with Disease Onset and Progression in Breast Cancer
ISR-affiliated Associate Professor Jaydev Desai (ME) is co-leading a cross-disciplinary team of researchers in a 5 year, $1.6M project to develop new approaches and technologies to provide new insight regarding the underlying mechanisms associated with disease onset and progression in breast cancer, not available using traditional assessment techniques.
FDA Safety and Performance Assessment of Emerging Autonomous Neonatal Ventilators by State-of-the-Art Robust Analysis Methods
Associate Professor Benjamin Shapiro (BioE/ISR) an inaugural University of Maryland Center of Excellence in Regulatory Science and Innovation (UM-CERSI) Innovation Awards. These one-year grants support collaborative research projects fostering regulatory science development in medications and/or medical devices. Shapiro received the award for "FDA Safety and Performance Assessment of Emerging Autonomous Neonatal Ventilators by State-of-the-Art Robust Analysis Methods." The project will apply and develop use-control verification techniques, specifically robust analysis, to initiate best safety practices in autonomous ventilators for preterm neonatal patients.
Collaborative Evaluation of Emerging Plasmonic Technologies for Point-of-Care Diagnostics in Low-Resource Settings
ISR-affiliated Assistant professor Ian White (BioE) has received one of four inaugural University of Maryland Center of Excellence in Regulatory Science and Innovation (UM-CERSI) Innovation Awards. These one-year grants support collaborative research projects fostering regulatory science development in medications and/or medical devices. White received an award for "Collaborative Evaluation of Emerging Plasmonic Technologies for Point-of-Care Diagnostics in Low-Resource Settings." The project focuses on the development of paper-based, surface enhanced Raman scattering (SERS) assay for viral diagnostics.
AFOSR: Multi-sensory integration for flight control
The sensory world of animals is noisy, complex and dynamic. From a barrage of stimuli, animals must detect, sort, group and track biologically relevant signals to communicate with conspecifics, seek food, engage in courtship, avoid predators and navigate in space.
Successful foraging by echolocating bats requires multimodal integration of visual, auditory, and somatosensory (e.g., tactile, proprioceptive) information, which is then used to drive adaptive motor behaviors in a dynamic environment. Executing complex flight maneuvers requires rapid sensory integration to generate adaptive motor output. In bats, the only mammals capable of powered flight, wing hairs provide somatosensory information to guide motor behavior. However, peripheral inputs and outputs to flight-related sensorimotor circuitry have not been studied. The goal of this project is to elucidate the neuroanatomical basis and functional role of this specialized airflow-detecting sensory substrate for stable and maneuverable flight. This is a five-year grant.
ADAM: The Adaptive Auditory Mind
Professor Shihab Shamma (ECE/ISR) is the principal investigator on a five-year, €3.3M project funded by the European Research Council’s (ERC) Advanced Grants Program. He is working with the Ecole Normale Supérieure and co-PI Daniel Pressnitzer, a researcher at the Laboratoire Psychologie de la Perception of the Centre National de la Recherché Scientifique. “ADAM: The Adaptive Auditory Mind” experimentally investigates a radically novel view of hearing, where active hearing emerges from a deep interplay between adaptive sensory processes and goal-directed cognition.
Paper-based surface enhanced Raman spectroscopy (P-SERS) for biosensing using inkjet-fabricated devices
ISR-affiliated Assistant Professor Ian White (BioE) is the recipient of a 2012 National Science Foundation Faculty Early Career Development (CAREER) Award for "Paper-based surface enhanced Raman spectroscopy (P-SERS) for biosensing using inkjet-fabricated devices." The five-year award is worth $400,000. White will develop a method to print sensitive, portable and inexpensive biosensors using ordinary inkjet printers.
NSF Collaborative Research: A General Theory of Group Testing for Genotyping
Professor Alexander Barg (ECE/ISR) is the principal investigator for a new NSF collaborative research grant, A General Theory of Group Testing for Genotyping. The three-year, $250K grant will fund the development of a comprehensive, yet analytically or computationally tractable general theory of group testing for genotyping. Barg’s proposed theory will answer the unique challenges arising in genotyping by sequencing. In addition to genotyping applications, parts of the theory also may find independent applications in areas as diverse as constrained multiple access channel analysis, fingerprinting and identification coding, and error-control coding. Several new models will be introduced into the field of group testing, including subjects with different types and strengths, semi-quantitative testing, two-dimensional pooling, and Poisson probabilistic testing.
Developing Scientifically-Based Consensus Food Safety Metrics for Leafy Greens and Tomatoes
ISR-affiliated Professor Benjamin Kedem (Math) is a co-investigator on a four-year, $5.4 million U.S. Department of Agriculture/National Institute of Food and Agriculture grant for "Developing Scientifically-Based Consensus Food Safety Metrics for Leafy Greens and Tomatoes." The principal investigator is Professor Robert L. Buchanan, director of the University of Maryland’s Center for Food Safety and Security Systems (College of Agriculture and Natural Resources).
Ordered Metrics and Their Applications
Professor Alexander Barg (ECE/ISR) is the principal investigator for Ordered Metrics and Their Applications. The three-year, $472K grant will fund research into the properties and applications of polar codes for communication systems. Polar codes are a new method of coding information for transmission over noisy channels that for the first time realizes the full potential of Shannon’s theorems related to data rate and transmission reliability. Polar codes have been shown to advance a range of classical and new information-theoretic problems that rely on efficient encoding of the data. Barg’s project addresses the properties of polar codes in nonbinary communication channels, the design of optimal polarizing transformations, and applications to unequal error protection, hierarchical source coding, broadcast channels, signal design, and other problems of importance for network communication.
Cooperating Camera Platforms for Ultra High Resolution Traffic Surveillance and Autonomous Event Detection
ISR-affiliated Professor Christopher Davis (ECE) and Professor Stuart Milner (CEE) are the principal investigators on a three-year, $1M contract from the Federal Highway Administration project to develop cooperating high definition cameras to monitor traffic characteristics, such as vehicle speeds and types, incidents, and congestion in the transportation infrastructure. The research will provide much-improved cooperating camera traffic surveillance.
Laser Beam Propagation through the Low Atmosphere in Deep Turbulence
ISR-affiliated Professor Christopher Davis (ECE) has been awarded a Multidisciplinary Research Initiatives (MRI) contract worth $4M over five years from the Joint Technology Office, “Laser Beam Propagation through the Low Atmosphere in Deep Turbulence.” Professor Davis will partner with Professor Thomas Antonsen (ECE/Physics/IREAP), Professor Stuart Milner of the Department of Civil and Environmental Engineering, and Professors Ron Phillips and Larry Andrews from the University of Central Florida. The research aims to develop new and improved techniques for characterizing the optical properties of the turbulent atmosphere along lengthy paths close to the ground. Such paths are described as involving “deep turbulence.” The ultimate goal is to provide improved information to adaptive optics systems that are used to project high energy laser beams at targets.
Minimally Invasive Neurosurgical Intracranial Robot
ISR and Maryland Robotics Center-affiliated Associate Professor Jaydev Desai (ME) and his colleagues from the University of Maryland, Baltimore (UMB) have won a $2 million grant from the National Institutes of Health (NIH) to continue developing a small robot that could one day aid neurosurgeons in removing difficult-to-reach brain tumors. A "Minimally Invasive Neurosurgical Intracranial Robot" (MINIR) prototype has been developed over a number of years and its feasibility already has been demonstrated, supported in part by a previous NIH grant. The research team consists of Desai and two faculty members of the University of Maryland School of Medicine at the University of Maryland, Baltimore: Associate Professor of Diagnostic Radiology and Nuclear Medicine Rao Gullapalli, M.D., and Professor of Neurosurgery J. Marc Simard, M.D.
Active Skins for Simplified Tactile Feedback in Robotics
Assistant Professor Sarah Bergbreiter (ME/ISR) is the principal investigator for a new National Robotics Initiative grant, “Active Skins for Simplified Tactile Feedback in Robotics.” The research project is one of eight selected by the National Aeronautical and Space Administration (NASA) as part of the initiative. Bergbreiter’s project will support NASA’s future missions in space. The National Science Foundation (NSF) managed the solicitation of proposals and participated in the peer review selection process. Awards range from $150,000 to $1 million, with a total of $2.7 million to be invested in the eight winning projects.
Multilingual Gestural Models for Robust Language-Independent Speech Recognition
Professor Carol Espy-Wilson (ECE/ISR) is the principal investigator for a two-year, $600,000 National Science Foundation Collaborative Research award, “Multilingual Gestural Models for Robust Language-Independent Speech Recognition.” This multi-site grant includes researchers at the Stanford Research Institute (SRI), Boston University and Haskins Laboratories. Espy-Wilson’s former student Vikramjit Mitra (EE Ph.D. 2011) is the principal investigator on the portion of the grant going to SRI. The researchers will develop a large-vocabulary speech recognition system based on articulatory information.
NSF Collaborative Research: Computational Foundations for Learning, Verifying, and Applying Model Simplification Rules
The researchers will develop feature-based simplification of computer-aided-design models, specifically to accelerate and automate downstream finite-element-analysis. In particular, the research will create algorithmic foundations for learning conservative feature suppression rules from demonstrations performed by human experts. The effect of simplification on simulation accuracy will be formally characterized and this understanding will be used to create robust algorithms for feature suppression within computer-aided design models. Research findings will be integrated into graduate and undergraduate curriculum. The research will ultimately lead to a framework to automatically learn, validate, and apply context dependent model simplification rules that can be audited by human experts, and deployed to automate the model simplification task.
The research will significantly speed up model simplification, and enhance the automated use of engineering analysis tools in the design process. Potential applications include design of heat exchangers, aircraft structures, and semi-conductor equipment. Computational Foundations for Learning, Verifying, and Applying Model Simplification Rules is a three-year, $265K award.
Physically Unclonable Function (PUF) Enhancements Via Lithography and Design Partnership
Associate Professor Ankur Srivastava (ECE/ISR) is the principal investigator of a three-year, $500K hardware security grant from the National Science Foundation for “Physically Unclonable Function (PUF) Enhancements Via Lithography and Design Partnership.” A silicon physically unclonable function (PUF) is a supplemental circuit embedded in an IC which generates signatures unique to its native IC. This research investigates fundamentally different approaches to PUF enhancements. It leverages quantified models for fabrication randomness that have been developed in design for manufacturability related research endeavors.
NSF CMMi: Mimicking How the Fly Hears: a New Approach Towards Sound Source Localization
The research will further the fundamental understanding of the dual optimality characteristic of the super acute ear of the fly Ormia, and to use this understanding to develop novel fly-ear inspired sensor systems with optimal performance and tuning capabilities. The proposed approach is summarized as follows. First, the advantageous use of geometric nonlinearity of the sensor structure whose stiffness will be controlled by thin film piezo-electric actuators will be investigated. This approach will render sensors with unique frequency tuning capabilities for achieving optimal performance over a broad frequency range. Further, a system-on-a-chip optical detection system featuring a differential low coherence interferometric system will be developed, which enables the miniaturization of the entire sensing system. Finally, to best use the proposed sensor, biologically-inspired adaptive sound source localization and navigation will be investigated. Such an investigation is expected to help understand the fly's unique localization-lateralization scheme and bring about a new sensing paradigm for miniature robotic sound source localization.
This research holds a promise to significantly impact applications in health care, safety, and defense.
Mimicking How the Fly Hears: a New Approach Towards Sound Source Localization is a four-year, $314K award.
DURIP: Research in audio-visual saliency and attention
Professor Shihab Shamma (ECE/ISR) received an award from the Office of Naval Research for "Research in audio-visual saliency and attention."
Distributed Function Computation and Multiterminal Data Compression
This research addresses the theory and design of algorithms for an efficient local computation by multiple network terminals of shared functions of all their observed correlated data. Efficient communication among the terminals facilitates efficient computation. Applications include: computing the average, variance, maximum, minimum and parity of observed data in a colocated network of wireless sensors that make correlated measurements. This objective is connected closely to the design of algorithms for the efficient compression of data for storage and transmission purposes, as well as of algorithms for assuring data security. A main goal of the project is to characterize explicitly these connections, thereby leading to the development of new and efficient algorithms for data compression, function computation and network security.
The technical approach involves a formulation of the underlying problems and their analysis, using an information theoretic framework. This will enable the development of a principle of "entropy decomposition of total shared randomness" in a network model to address difficult problems in multiuser information theory of which rate-efficient function computation is a leading example. In particular, an application of source coding algorithms in distributed function computation will be studied. Specific groups of open problems chosen for investigation address a general class of multiterminal models for function computation and data compression. This choice is motivated by the theory and engineering practice of network function computation and source coding, as well as network security.
The ideas were developed jointly with Ph.D. student Himanshu Tyagi.
DURIP: Optical stimulation to probe function and structure of microcircuits in auditory cortex of the brain
ISR-affiliated Assistant Professor Patrick Kanold (Biology) received an Air Force Office of Scientific Research award for “Optical stimulation to probe function and structure of microcircuits in auditory cortex of the brain.”
Developing and Applying Reuse Distance Analysis Techniques for Large-Scale Multicore Processors
Associate Professor Ankur Srivastava (ECE/ISR) and Associate Professor Donald Yeung (ECE) have won a three-year, $500K grant for “Developing and Applying Reuse Distance Analysis Techniques for Large-Scale Multi-core Processors.” The award is being funded through the National Science Foundation’s Software and Hardware Foundations (SHF) program within the Division of Computing and Communication Foundations (CCF). Yeung is the principal investigator. The research will address concerns in multi-core and many-core architecture by exploring research directions related to multi-core reuse distance (RD) analysis for loop-based parallel programs.
Remote Imaging of Community Ecology via Animal-borne Wireless Networks
Associate Professor Nuno Martins (ECE/ISR) is the principal investigator of a new National Science Foundation Cyber-Physical Systems grant, "Remote Imaging of Community Ecology via Animal-borne Wireless Networks.” The research will develop autonomous systems that monitor and protect endangered animal species. The four-year, $1.8M grant is a collaborative proposal with the National Geographic Society and ECE/ISR alumna Naomi Leonard at Princeton University. Leonard’s Ph.D. advisor at Maryland was Professor P.S. Krishnaprasad (ECE/ISR). The researchers will construct a wireless network of animal-borne embedded devices deployed and tested in a biologically-relevant application. The networked devices will provide geo-location data and execute cooperative strategies that save battery life by selectively recording bandwidth-intensive audio and high-definition video footage of occurrences of animal group behavior of interest, such as predation.
First-Principles Based Control of Multi-Scale Meta-Material Assembly Processes
Associate Professor Benjamin Shapiro (BioE/ISR) is a principal investigator on a new National Science Foundation grant to develop tools that could one day mass-produce revolutionary materials for future technologies such as optical computing, energy harvesting, sub-diffraction limit imaging and invisibility cloaking. “First-Principles Based Control of Multi-Scale Meta-Material Assembly Processes,” is a four-year, $1.6 M Collaborative Research Cyber-Enabled Discovery and Innovation (CDI) Type II grant that focuses on precisely controlling ensembles of nanoparticles to create defect-free crystals for optoelectronic metamaterials, in a way that has the potential to scale up to fabrication. Such a development could have a similar revolutionary effect as the creation of single crystal silicon, which enabled integrated circuits and modern computing.
NSF: Design-for-Availability: Designing Safety, Mission and Infrastructure Critical Systems to Meet Availability Targets
The objective of this research award is to develop a new methodology that uses an availability requirement as an input to the process of determining the optimal design and management of a system. Availability is the ability of a service or a system to be functional when it is requested for use or operation. Availability depends on an item's reliability (how often it fails) and maintainability (how efficiently it can be restored when it does fail). Availability is a significant issue for many systems including: ATM machines, point-of-sale systems, medical equipment, wind farms, military systems and airlines. For these safety, mission, and infrastructure critical systems, customers are often interested in buying the availability of a system through 'availability contracts' instead of actually buying the system itself. This research will develop a design for availability methodology applicable to single and multiple design parameters, perform model verification, integrate the model with life cycle cost analyses, and apply the model to logistics and reliability parameters, and within Prognostics and Health Management (PHM) environments.
This research will provide a significant new capability to: a) perform real-time pro-active availability analysis; b) determine requirements 'flow down' to supply chains; and c) perform pro-active reliability versus logistics tradeoffs, and assess the cost and resources required to deliver and support systems subject to availability contracts.
Design-for-Availability: Designing Safety, Mission and Infrastructure Critical Systems to Meet Availability Targets is a four-year, $300K award.
Cooperative Agreement: Cyber-Physical Systems
Professor John Baras (ECE/ISR) is the principal investigator for a $1 million cooperative agreement with the National Institute of Standards and Technology. Associate Professor Mark Austin (CEE/ISR) and ISR postdoctoral researcher Shah-An Yang are co-principal investigators on the agreement. The research team will help NIST develop and deploy standards, test methods, and measurement tools to support consistently reliable performance of new smart systems. These cyber-physical systems (CPS) knit information and physical technologies into interactive, self-optimizing products and infrastructures ranging from smart cars, aircraft and buildings to an intelligent electric power grid. By developing standards, test methods, and measurement tools, the UMD/NIST effort can help U.S. industry accelerate development of innovative cyber-physical system products that create jobs, while also protecting these new types of CPS infrastructure from cyber threats.
NSF: Nonlinear Signal Processing and Distributed Optimal Control using Frames and Operators Algebras
This research will study new methods to recover a signal from a nonlinear processing scheme. Recently two far-reaching discoveries have been made that connected the nonlinear information (magnitudes of frame coefficients) to certain scalar products in larger embedding spaces. Thus the initial problem, which is fundamentally nonlinear, is recast into a linear reconstruction problem coupled with a rank-one approximation problem. When the linear redundant representation is associated with a group representation (such as Weyl-Heisenberg, or windowed Fourier transform), then the relevant tensor operators inherit this invariance property. Thus a fast (nonlinear) reconstruction algorithm is possible. This approach suggests a new signal representation model, where signals are not represented simply by vectors in a Hilbert space, but rather by operators in a larger dimensional Hilbert-Schmidt like-space, similar to the quantum state theory. These methods use results from a wide range of mathematical areas such as harmonic analysis, operator theory, and polynomial algebras.
Results of this project have a practical application to areas such as signal processing, optical communication, quantum computing, and X-ray crystallography.
Nonlinear Signal Processing and Distributed Optimal Control using Frames and Operators Algebras is a four-year, $250K award.
Energy-Efficient Cognitive Networking
Professor Tony Ephremides (ECE/ISR) is the principal investigator for a new National Science Foundation collaborative research grant, “Energy-Efficient Cognitive Networking.” The two-year, $172,860 grant is a special project of NSF’s Computer & Information Science & Engineering directorate. The research will consider energy efficiency for cognitive radio networks and introduces a novel optimization-based methodology. It builds on existing results to establish a new focus on green cognitive networking.
Robust and Secure Cognitive Radio Networks
Professor Sennur Ulukus (ECE/ISR) is the principal investigator for a new National Science Foundation collaborative research grant, “Robust and Secure Cognitive Radio Networks.” The grant is a special project of NSF’s Computer & Information Science & Engineering directorate, and part of a new US-Finnish collaboration program. Maryland’s portion of the grant is for two years and $160,000. Effective coexistence of secondary users is essential for the success of future cognitive networks. In addition, the particularly open nature of cognitive radio raises significant new issues for the security and privacy of the transmitted data, as well as new opportunities for malicious behavior among cognitive or outside entities. The project addresses these issues in a holistic framework.
Broadband Internet-via-Satellite System
Professor John Baras (ECE/ISR) is working with Frederick, Md.-based Cerona Networks on research funded by a $268,600 MIPS grant. The team will develop a broadband Internet-via-satellite system with two-way performance that approaches terrestrial Internet connections. The system will save costs for providers and can be retrofit to existing systems.
OmniSpeech Performance Improvement
Professor Shihab Shamma (ECE/ISR) is working with College Park-based OmniSpeech LLC on research funded by a $135,000 MIPS grant. The research will improve the performance of software that separates speech from background noise for clear cellular and other communications.
Microrobot Legs for Fast Locomotion over Rough Terrain
Assistant Professor Sarah Bergbreiter (ME/ISR) is the recipient of a 2011 National Science Foundation Faculty Early Career Development (CAREER) Award for "Microrobot Legs for Fast Locomotion over Rough Terrain." The five-year award is worth $400,000. Bergbreiter will create legs that will enable microrobots to walk, and even run, over rough terrain. She will model viscoelastic microrobot legs in a dynamic simulation environment and experimentally validate the models using a new microfabrication process that includes viscoelastic materials.
Neuromechanics and Dynamics of Locomotion
Professor Avis Cohen (Biology/ISR) is a co-PI on a five-year, $500K National Science Foundation (NSF) grant award from the Research Coordination Networks Physical/Life Sciences (RCN-PLS) program, "Neuromechanics and Dynamics of Locomotion." Lisa Fauci of Tulane University is the principal investigator. Locomotion is a prime example of how the nervous system creates a complete behavior. Relationships among neuronal and motoneuronal activities, and the resulting dynamic muscle forces need to be deduced, then how muscle forces combine with the mechanics of the organism in its environment is described. Finally, the integration of sensory feedback into movement control must be described.
Neural Basis for Working Memory
ISR Associate Research Scientist Jonathan Fritz received a $150K seed grant from the Office of Naval Research for a one-year study that will lay the groundwork for exploring the neural basis for working memory. Working memory is one of the forms of memory essential for cognitive processing as we hold one image, sound or idea in mind despite the presence of other competing or distracting stimuli.
The University of Maryland is the lead institution for an eight-university consortium forming NEXTOR II, a research program focused on aviation operations research. The new seven-year contract with the Federal Aviation Administration (FAA) will extend and expand the work of the original National Center of Excellence for Aviation Operations Research (NEXTOR). Research expenditures could total as much as $60M over the length of the contract. ISR professors Michael Ball (ISR/Robert H. Smith School of Business) and David Lovell (ISR/CEE) lead the Maryland NEXTOR II team.
Component Based Routing and Clique Based Scheduling for Modular Cross-layer Design of Mobile Ad-Hoc Networks
Professor John Baras (ECE/ISR) has been awarded a new National Science Foundation (NSF) Networking Technology and Systems (NeTS) grant for “Component Based Routing and Clique Based Scheduling for Modular Cross-layer Design of Mobile Ad-Hoc Networks.” The grant will provide $470,000 in funding over three years. Dr. Vahid Tabatabaee, the co-PI, was co-advised by former ECE/ISR faculty member Leandros Tassiulas and Dr. Baras. The research project provides a new framework for modular cross-layer design of scheduling and routing algorithms for ad-hoc networks. Efficient routing and scheduling algorithm for ad-hoc networks are among the most challenging network problems. The proposed research re-examines some of the basic assumptions of wireless network design.
An AFOSR four-year collaborative project, devoted to the investigation of principles and algorithms that underlie purposeful collective behavior in natural and engineered systems, involves P.S. Krishnaprasad (ECE/ISR) and Andrea Cavagna of the Institute for Complex Systems, of the Italian National Research Council. Building on their separate prior contributions, Krishnaprasad and Cavagna have launched an intense program of research in natural flocks and swarms of birds and insects. The research is aimed at discerning the underlying principles, working out models and algorithms to create quantitative support for the extracted principles, and exploiting the resulting understanding, as codified in models and algorithms, in the design, implementation and verification of robust, distributed, cooperative, survivable control systems for swarms of autonomous robots. A variety of tools from geometric and optimal control theory, statistical physics, graph theory, and large-scale data analysis coupled with empirical observations, will be brought to bear on problems of collective behavior, to elucidate the scientific foundations of the subject, and realize applications to robotics.
Forensic Hash for Assured Cyber-Based Sensing and Communications
Associate Professor Min Wu (ECE/UMIACS) has been awarded an NSF grant for "Forensic Hash for Assured Cyber-Based Sensing and Communications." This grant provides $344K support over three years. The objective of this research is to address the challenge in trustworthy sensing and communications, as content-rich audio-visual streams become increasingly adapted on-the-fly for individual receivers. The proposed project develops a novel framework of Forensic Hash for Information Assurance. Offering more forensic answers about data integrity, origin, and processing history in higher accuracy and efficiency, the proposed framework overcomes the current one-size-fit-all dilemma and enables trust assessment at a higher level.
Cooperative Research and Development Agreement: RDECOM
The University of Maryland and the U.S. Army Research, Development and Engineering Command (RDECOM) officially joined forces to expand research, development and engineering efforts by signing a Cooperative Research and Development Agreement (CRADA) in September. The CRADA builds upon already existing working relationships with the university while increasing the understanding of the transforming missions and functions of Aberdeen Proving Ground, where RDECOM is headquartered. The ceremony took place in the rotunda of the Jeong H. Kim Engineering Building.
Adaptive perceptual-motor feedback for the analysis of complex scenes
Professor Cynthia Moss (Psych/ISR) is the principal investigator and Associate Professor Timothy Horiuchi (ECE/ISR) is the co-PI for a new National Science Foundation Collaborative Research in Computational Neuroscience grant, "Adaptive perceptual-motor feedback for the analysis of complex scenes." The five-year, $1.5 million grant will fund research to understand the processes that support perception and action in complex settings. The research will focus on spatial perception and navigation in the echolocating bat, an auditory specialist that produces high frequency sonar calls and listens to echo returns to determine the location of objects in its environment. The echolocating bat modifies its sonar calls in response to echo information from targets (insect prey) and obstacles. Quantitative analyses of this animal's adaptive vocal behavior will be used to infer its perception of a changing environment.
Information Hiding Based on Trusted Computing System Design
Associate Professors Gang Qu (ECE/ISR) and Min Wu (ECE/UMIACS) have received a grant from the Air Force Office of Scientific Research (AFOSR) for research on information hiding based trusted computing system design. Qu is principal investigator (PI) and Wu is co-PI for this 3-year $450K effort that aims at enhancing the trust in systems designed and implemented by untrusted parties. The research investigates a novel information hiding framework based on constraint manipulation techniques to facilitate the verification of the non-existence of undesired functionality in the system.
NSF: Resilience in Rail-Based Intermodal Transportation Systems: Performance Measurement and Decision Support
Risks from accidents, weather-induced hazards, and terrorist attacks on freight and passenger transport systems have dramatically increased in recent years. The occurrence of such events can have tremendous impact on system performance, especially intermodal (IM) systems, and can lead to significant economic loss. A secure and functioning transportation system is of paramount importance to society. To ensure that effective transport services can be provided in a disaster's aftermath, enabling society to recover, agencies charged with constructing, managing and operating these systems must invest in measures that prevent or mitigate the effects of disaster incidents. This research effort recognizes that the post-disaster performance of transportation networks depends not only on the inherent capability of the system to absorb externally induced changes, but also on the actions that can be taken in the immediate aftermath of the disaster to preserve or restore system performance. Identification of the appropriate pre-event preparatory and post-disaster recovery actions and related investment allocation decisions can play a crucial role in lessening ensuing post-disaster economic and societal loss. This effort will provide a comprehensive set of tools, that explicitly consider opportunities for post-disaster recovery activity, to support rail-based IM system performance measurement, operational decision-making, preparedness planning and immediate post-disaster action. The development of such tools requires the mathematical modeling of complex dynamic and stochastic systems and creation of exact algorithms and faster heuristics for solution of large-scale real-world problems. Developed tools will aid the managers of these critical lifelines to effectively address threats from disasters. While results of this effort will have wide applicability, its focus is on rail-based IM passenger and freight transport systems and their components (e.g. passenger depots, IM terminals, ports).
The performance measurement, preparedness planning and operational decision-making tools developed through this effort will provide support to infrastructure managers and IM system operators of rail-based IM passenger and freight transport systems, facilitating optimal investment decisions aimed at preventing or ameliorating the effects of disasters. Application of these tools will aid in securing the IM transport networks and address society's need for a stable system.
Resilience in Rail-Based Intermodal Transportation Systems: Performance Measurement and Decision Support is a five-year, $421K award.
Supercomputer Prototype Systems
ISR-affiliated Assistant Professor Bruce Jacob is part of a team selected by the Defense Advanced Research Projects Agency (DARPA) to develop new supercomputer prototype systems for DARPA's Ubiquitous High Performance Computing (UHPC) program. The 4-year, $25.8M award will fund research at the University of Maryland, as well as academic project partners at Louisiana State University, University of Illinois at Urbana-Champaign, University of Notre Dame, University of Southern California, Georgia Institute of Technology, Stanford University and North Carolina State University. Sandia Laboratories, a wholly owned subsidiary of Lockheed Martin company, is leading a team of industry partners on the project, including Micron Technology, Inc. and LexisNexis Special Services, Inc. The goal is to overcome current limiting factors, such as power consumption and architectural and programming complexity, by developing entirely new computer architectures and programming models. The program aims to produce a more energy-efficient computer that delivers 100 to 1,000 times more performance and is easier to program than current systems.
Nonlinear Problems of Solid Mechanics
ISR-affiliated Professor Stuart Antman (Math) received a one-year, $123K NSF grant for Nonlinear Problems of Solid Mechanics. The investigator gives careful mathematical treatments of a variety of dynamical and steady-state nonlinear problems for deformable rods, shells, and three-dimensional solid bodies, possibly in contact with moving fluids, variable temperature fields, and electromagnetic fields. The bodies are composed of nonlinearly elastic, plastic, viscoplastic, or magneto-(visco-)elastic materials. The goals of these studies are to discover new nonlinear effects and new kinds of instabilities, determine thresholds in constitutive equations separating qualitatively different responses, determine general classes of constitutive equations that are both physically and mathematically natural, determine how existence, regularity, and well-posedness depend on material behavior, contribute to the theory of shocks and dissipative mechanisms in solids, and develop new methods of nonlinear analysis and of effective computation for problems of solid mechanics.
Delay Minimization in Wireless Networks
Associate Professor Sennur Ulukus (ECE/ISR) is principal investigator for “Delay Minimization in Wireless Networks.” The grant will provide $250,000 in funding over three years. This project aims to develop a fundamental understanding for the issue of delay in networks, and design transmission methods and scheduling algorithms to minimize delay in network communications. It combines techniques from information theory, network theory, queueing theory and optimization theory.
Dexterous Fiber Optic Tweezers for Bio-Particle Manipulation and Force Sensing
ISR-affiliated Associate Professor Miao Yu (ME) has won a three-year, $200K NSF grant for Dexterous Fiber Optic Tweezers for Bio-Particle Manipulation and Force Sensing. The objective of this research project is to develop a dexterous dual fiber tweezers system with greatly enhanced flexibility, functionality, and efficiency. The novel fiber optical tweezers equipped with surface plasmonic lens will significantly enhance the trapping efficiency compared with conventional fiber tweezers. This effort is expected to not only enrich the fields of sensors, actuators, and biophotonics, but also pave the way for developing innovative tools for the study of biological systems, and shed further light on pathological mechanisms and disease diagnosis.
Associate Professor Sennur Ulukus (ECE/ISR) is principal investigator for a four-year, $1.1 million NSF grant, “Interactive Security.” This is a joint grant with Prof. Aylin Yener of Penn State University and Prof. Kannan Ramchandran of the University of California, Berkeley. The research aims to secure wireless communication channels in the physical layer using techniques from information theory, communication theory, and signal processing. The researchers plan to use the unique characteristics of the wireless medium to secure the communication.
An Approach to Semiparametric Regression with Random Covariates
ISR-affiliated Professor Ben Kedem (Math) has received a three-year, $100K NSF grant for An Approach to Semiparametric Regression with Random Covariates. Given multiple multivariate data sources, each represented by an unknown multivariate distribution, the investigator proposes an approach to regression analysis based on relationships between semiparametric estimates of these multivariate distributions. Resulting from this are regression estimates expressed as estimates of the conditional expectation of a response given its covariates, for each source. The investigator plans to study the statistical properties of the regression estimates, associated diagnostic tools, the applicability and computability of the method using real data, and compare the method to multiple and kernel regression methods.
Dynamics and Control of Motion Coordination for Information Transmission in Groups
ISR-affiliated Assistant Professor Derek Paley (AE) has won a $400,000 National Science Foundation Early Faculty Career (CAREER) Award for Dynamics and Control of Motion Coordination for Information Transmission in Groups. Paley will study information transmission in biological groups (like schools of fish) and apply the same principles to design motion coordination strategies for autonomous vehicles. Specifically, Paley's research will improve understanding of information transmission in biological groups and apply this understanding to synthesize bio-inspired motion-coordination algorithms for autonomous vehicles.
Robots with Vision that Find Objects
ISR-affiliated Professor Yiannis Aloimonos has been awarded a three-year, $550K NSF Cyber-Physical Systems Methods and Tools grant, "Robots with Vision that Find Objects." The objective of this research is the development of methods and software that will allow robots to detect and localize objects using Active Vision and develop descriptions of their visual appearance in terms of shape primitives. The approach is bio inspired and consists of three novel components.
Associate Professor Sennur Ulukus (ECE/ISR) has been awarded a new NSF grant, “Rechargeable Networks.” The four-year, $900,000 award is a joint grant with Roy Yates of Rutgers University andAylin Yener of Penn State University. The project examines wireless communication networks whose nodes have batteries that recharge by harvesting energy from the environment. It applies analytical models for battery recharging to evaluate fundamental multiple access, broadcast and relay network models composed of rechargeable nodes. The project objective is an enhanced understanding of the analytic fundamentals of rechargeable networks in order to contribute to the development and ultimate deployment of ecologically-friendly rechargeable networks.
MURI: Multi-layer and multi-resolution Networks of Interacting Agents in Adversarial Environments
Supporting A Nation of Neighbors with Community Analysis Visualization Environment
ISR-affiliated Professor Ben Shneiderman (CS/UMIACS) has been awarded a one-year, $250K NSF Social-Computational Systems grant for "Supporting a Nation of Neighbors with Community Analysis Visualization Environment." Computationally-mediated civic participation is emerging as a solution to contemporary problems associated with economic and social issues such as healthcare, energy sustainability, education, environmental protection, and disaster response. The NSF-funded research project conducted by Ben Shneiderman, Alan Neustadtl, and Catherine Plaisant at the University of Maryland will study reasons for successes and failures of the community safety system, Nation of Neighbors. The results will enable interventions to shift the balance towards increasing success.
Vicon real-time optical tracking system
Professor Cynthia Moss (Psychology/ISR) has won a $200K Defense University Research Instrumentation Program (DURIP) award from the Air Force Office of Scientific Research (AFOSR). The DURIP award will be used to purchase a Vicon real-time optical tracking system and multichannel acquisition processor system (MAP) for Moss’s study of the role of bat wing hairs in flutterig membrane, and also to study somatosensory signang flight control. The MAP system will allow Moss and her research team to follow single neurons over time, before and after epilation of the winling.
Science of Integration for Cyber-Physical Systems
Professor John Baras (ECE/ISR) is a co-PI on a new five year, $4,997,185 National Science Foundation (NSF) grant award from the Cyber-Physical-Systems (CPS) program in the large category, "Science of Integration for Cyber-Physical Systems." The University of Maryland share for the five years is $1,237,500. The project will develop a new Science of Integration for Cyber Physical Systems (CPS), re-examining the fundamentals of composition in heterogeneous systems, developing foundations and tools for system integration and validating the results in experiments using automotive and avionics System-of-Systems experimental platforms. The new Integration Science represents a major departure from the current discipline-oriented, compartmentalized systems design. Building on a rigorous theory, it will develop the foundations, and methods and tools for achieving constructivity and predictability in CPS integration.
Systems Engineering Research Center (SERC)
The Institute for Systems Research is the lead University of Maryland unit, representing the University of Maryland, as a collaborator and partner in the University Affiliated Research Center (UARC), Systems Engineering Research Center (SERC). SERC is a consortium of 20 universities, with Stevens Institute of Technology as the lead, funded by the DDR&E. The University of Maryland became a partner and collaborator of SERC in March 2010. Professor John Baras (ECE/ISR) is the Principal Investigator for Maryland. SERC leverages the research and expertise of senior lead researchers from collaborator universities and not-for-profit research organizations throughout the United States—a community of broad experience, deep knowledge, and diverse interests.
ADVANCE Program for Inclusive Excellence
Professor Avis Cohen (Biology/ISR) is the program director for a new University of Maryland program funded by the National Science Foundation. The five-year, $3.2 million ADVANCE Program for Inclusive Excellence seeks to increase the representation of women faculty members in science, technology, engineering, and mathematics (STEM) fields at the university. Building on the university’s achievements in inclusiveness and equity, the ADVANCE program will implement interconnected strategies designed to transform academic environments and promote the professional growth of women faculty in STEM.
Quantum Computing: Improving Josephson Junction Qubits
Professor Gary Rubloff (MSE/ISR) is the co-PI on an interdisciplinary research collaboration with the Joint Quantum Institute (JQI) that has been awarded a five-year, $2.8 million grant from the Intelligence Advanced Research Projects Activity (IARPA) through the Army Research Office (ARO) to devise, fabricate, study and test a new kind of key component for quantum computing. The team will work on novel methods of constructing the crucial, ultra-thin insulating barrier that lies between two superconductors to form a "Josephson junction."
Network Pricing with Uncertainty: Risk Aversion and Incomplete Information
Associate Professor Richard La (ECE/ISR) received an NSF Theoretical Foundations grant for "Network pricing with uncertainty: risk aversion and incomplete information." The three-year, $300K grant will begin to identify suitable frameworks for designing efficient and fair network pricing mechanisms. The research will take the first step towards identifying suitable frameworks for designing efficient and fair network pricing mechanisms. It will help service providers identify more suitable pricing schemes that will encourage the deployment of new services through fair profit sharing and improved efficiency. This will promote collaboration among selfish service providers and bring more network services and lower prices to the consumers, while increasing the overall social benefits/welfare.
Optimization Algorithms for Large-scale, Thermal-aware Storage Systems
Associate Professor Ankur Srivastava (ECE/ISR) is a co-PI for a three-year, $900K National Science Foundation grant, "Optimization Algorithms for Large-scale, Thermal-aware Storage Systems." Professor Samir Khuller (CS/UMIACS) is the principal investigator, while Assistant Professor Amol Deshpande (CS/UMIACS) also is a co-PI. The researchers will investigate optimization problems that arise when managing the thermal requirements of very large data storage centers. This project seeks to develop a general science of thermal management for large scale storage systems, by focusing on thermal modeling and management at different levels of the system hierarchy.
Knowledge Representation and Design for Managing Product Obsolescence
ISR-affiliated Professor Peter Sandborn (ME) received an NSF collaborative research grant for Knowledge Representation and Design for Managing Product Obsolescence. The two-year, $105K grant will investigate two novel research approaches to understanding and managing technology obsolescence challenges. Sandborn will build a knowledge representation scheme and management system that can facilitate information sharing and collaboration for obsolescence management and mitigation efforts between existing tools and across different organizations. He also will develop fundamental principles, teachable methods, and guidelines for designing product architectures that can evolve with changing requirements, enabling proactive obsolescence management across the entire product life cycle. The research will provide an opportunity to create cost-effective, and environmental friendly products at faster pace.
NSF CIF: Information Theoretic Multi-Core Processor Thermal Profile Estimation
This research will provide a new approach to the problem of managing multi-core processor thermal sensors and processing their measurements. It will rely on fundamental information theoretic principles, new problems in information theory that capture the salient features of on-chip thermal profile estimation. The associated new formulations are inspired notably by rate distortion theory and also bear a similarity to compressed sensing. Furthermore, the approach has wider applicability to general problems of parameter estimation based on limited sampled and quantized measurements. The research will improve the performance and reliability of multicore processors; and introduce new models and problem formulations in the fields of information theory and compressed sensing.
Throughput Rates, Capacities, and Ultimate Capabilities for Wireless Networks with Bursty Traffic
The Office of Naval Research (ONR) awarded Professor Anthony Ephremides (ECE/ISR) a grant for “Throughput Rates, Capacities, and Ultimate Capabilities for Wireless Networks with Bursty Traffic.” Ephremides will use this one-year grant to research alternative measures of network ultimate capabilities and to develop new methods of analysis and evaluation.
Combining Gradient and Adaptive Search in Simulation Optimization
Professor Michael Fu (BMGT/ISR/ECE) is the principal investigator and Professor Steve Marcus (ECE/ISR) is the co-PI for a three-year, $350K NSF collaborative research grant, Combining Gradient and Adaptive Search in Simulation Optimization. The researchers will develop new simulation optimization algorithms based on different sequences of the so-called "reference distributions" in a recently developed approach called model reference adaptive search, and new hybrid global-local search algorithms integrating local gradient search and problem structure. They also will conduct rigorous theoretical analysis of the resulting algorithms, both finite-time behavior using an adaptive search framework and asymptotic behavior using a novel connection to stochastic approximation methods. A wide variety of applications from supply chain management to financial engineering will be tested to investigate specific gradient search algorithms and problem structure, and evaluating the effectiveness in terms of empirical behavior. This line of research fills an important part of the "analytics" computational tool kit that has led to increased competitiveness for US businesses from manufacturers and retailers with global supply chains to financial services managing complex risk factors.
Physical Systems Dynamics for the Characterization and Control of Complex Wireless Networks
ISR-affiliated Professor Christopher Davis (ECE) and Research Professor Stuart Milner (CEE) have received a two-year, $150K NSF grant for "Physical Systems Dynamics for the Characterization and Control of Complex Wireless Networks." The grant is part of NSF’s EAGER (EArly-concept Grants for Exploratory Research) program. Milner is the Principal Investigator (PI) for the grant. The EAGER project addresses the need for wireless networks to autonomously reconfigure themselves to adapt to changes in the network or in the requirements of the supported applications. The approach utilizes physics-based models for characterization and control that are inspired by the dynamics of multiple-connected atoms forming a molecular network.
Tribologically-Enhanced Encapsulated Microball Bearings for Reduced Friction and Wear in High-Performance Rotary Microactuators and PowerMEMS Devices
Professor Reza Ghodssi (ECE/ISR) received a three-year, $330,000 NSF grant for research on microball bearing systems with an emphasis on material interfaces for MicroElectroMechanical Systems (MEMS) applications. Ghodssi is the PI for "Tribologically-Enhanced Encapsulated Microball Bearings for Reduced Friction and Wear in High-Performance Rotary Microactuators and PowerMEMS Devices." The research will develop high-performance rotary ball bearings for MEMS using special, tribologically-enhanced thin-film coatings. Particular emphasis will be placed on the design, fabrication, and experimental characterization of the thin films as hard coatings to reduce friction and wear in microscale rolling contacts. The research will be implemented in a low-friction, low-wear, and long-lifecycle microball bearing for rotary microactuators and PowerMEMS devices.
New Approaches to the Design and Analysis of Graphical Models for Linear Codes and Secret Sharing Schemes
Professor Alexander Barg (ECE/ISR) is the principal investigator for a new NSF grant, New Approaches to the Design and Analysis of Graphical Models for Linear Codes and Secret Sharing Schemes. The three-year, $350K grant will fund new approaches to the design and analysis of graphical models for linear codes and secret sharing schemes. Error-correcting coding enables the design of reliable information transmission and storage systems. It also is universally used for sending packets of information over the internet, writing data on CDs and flash memory devices, and other similar means of modern communication. Barg’s research will devise new ways of constructing and analyzing the error-correcting schemes that are used for transmission.
A Micro-Direct Methanol Fuel Cell with Nanostructured Platinum Catalysts Using the Tobacco Mosaic Virus
Professor Reza Ghodssi (ECE/ISR) is the principal investigator for a $250,000 FY2009 Maryland Nanobiotechnology Research and Industry Competition Grant for “A Micro-Direct Methanol Fuel Cell with Nanostructured Platinum Catalysts Using the Tobacco Mosaic Virus.” The research will develop fuel cells with surface area nano-structured electrodes using the Tobacco mosaic virus. The TMV is a high aspect ratio plant nanostructure which can be genetically modified to include functional groups that facilitate electroless metal deposition and self-assembly onto gold surfaces. This biotemplating process has been integrated with standard micro-machining for the development of micro-fabricated batteries.
Advanced Optimization Techniques for Entropy-Based Moment Closures
Professor AndréTits (ECE/ISR) is the principal investigator and Professor Dianne O’Leary (CS/UMIACS) is the co-PI for a new Department of Energy grant, “Advanced Optimization Techniques for Entropy-Based Moment Closures.” The University of Maryland portion of the three-year grant is funded at $769,918, and the work is being done in collaboration with Dr. Cory Hauck of the Oak Ridge National Laboratory. The research team will design and implement advanced convex optimization methods for solving entropy maximization problems. In transport and kinetic theory, solutions to these problems are used to derive closures for moment models that inherit many fundamental features of kinetic transport. Specific applications include gas dynamics, radiative transfer, charged-particle transport, and neutron transport.
Science of Precision Multifunctional Nanostructures for Electrical Energy Storage
Former ISR Director and Professor Gary Rubloff (MSE/ISR) will lead a new Energy Frontier Research Center (EFRC) as part of a major new U.S. Department of Energy program. Rubloff, who directs the Maryland NanoCenter, will draw faculty groups from three colleges—The A. James Clark School of Enginering; Chemical and Life Sciences; and Computer, Math and Physical Sciences. EFRCs enlist the talents and skills of the very best American scientists and engineers to address current fundamental scientific roadblocks to U.S. energy security. The University of Maryland EFRC will address the "Science of Precision Multifunctional Nanostructures for Electrical Energy Storage." Its objective is to understand how nanostructures formed from multiple materials behave and their potential for a new generation of electrical energy storage technology. By using materials in precisely built nanostructures, energy storage devices will hold more energy, will charge or deliver electricity faster, and remain stable for longer lifetimes, while reducing space and weight.
NSF CIF: Nonintrusive Digital Speech Forensics: Source Identification and Content Authentication
Professor Carol Espy-Wilson (ECE/ISR) is the principal investigator for a three-year, $500K National Science Foundation grant, “Nonintrusive Digital Speech Forensics: Source Identification and Content Authentication.” With the advent of the digital era, virtually every speech communication system acquires, creates, transmits, stores, and processes information in digital form. Moreover, current digital media editing software allows malicious amateurs to perform imperceptible alterations to digital content. This creates a serious threat to the “knowledge life cycle.” When hearing is no longer believing, the process of going from data to information, knowledge, understanding and, finally, to decision or action is severely compromised. To help reduce this threat, Dr. Espy-Wilson will develop theories, methods and tools for extracting and visualizing evidence from digital speech content to identify the media source and authenticate content.
Distributed Learning and Information Dynamics in Networked Autonomous Systems
Professor John Baras (ECE/ISR), ISR Director Eyad Abed (ECE/ISR) and Assistant Professor Nuno Martins (ECE/ISR) will be participating in an Air Force Office of Scientific Research (AFOSR) MURI, "Distributed Learning and Information Dynamics in Networked Autonomous Systems." Maryland's portion of the award is $2.7 million. Georgia Tech is the lead institution, and Jeff Shamma, who was an ISR Distinguished Lecturer in February 2009, is the principal investigator. This award was made in MURI category 16: Learning Decision Architectures for Intelligent Cooperative Control of Autonomous Systems. The research will set a foundation that enables advanced operations of teams of autonomous vehicles to learn and adapt in uncertain and hostile environments while effectively using communications resources. The research will include studies of learning under sparse communications, game theoretic learning, and on-line formation of desirable network architectures. There will be implications for key problems in social, economic and biological networks.
NSF Collaborative Research: Targeting Observations of Tropical Cyclones using Cooperative Control of Unmanned Aircraft
The research will construct an analytical framework to reduce uncertainty in forecasts of hurricane intensity by optimally targeting a coordinated observing network of unmanned aircraft using ensemble-based adaptive sampling and coordination of sampling trajectories. An ensemble-based theory combined with serial adaptive sampling and rapid assimilation updates will be employed for the first time to yield probabilistic flow estimates and optimal sampling configurations. A new theory in decentralized motion coordination will be developed to account for spatially and temporally variable flow fields that exceed the platform speed relative to the flow. The framework will be evaluated using a hierarchy of hurricane models to assess improvements in probabilistic forecasts of the flow. The proposed research will achieve theoretical advances broadly applicable to environmental sampling, including ensemble-based assimilation of near-continuous data, ensemble-based adaptive sampling, and decentralized coordination of unmanned platforms in dynamic flow fields.
The broader significance of this research project lies in its potential to improve hurricane forecasts by integrating next-generation weather prediction models with novel strategies for adaptive motion coordination of multiple unmanned aircraft.
Targeting Observations of Tropical Cyclones using Cooperative Control of Unmanned Aircraft is a four-year, $275K grant.
NSF CPS: Ant-Like Microrobots—Fast, Small, and Under Control
A team of Clark School faculty from the Institute for Systems Research, the Electrical and Computer Engineering Department and the Mechanical Engineering Department has won a three-year, $1.5 million National Science Foundation grant for Ant-Like Microrobots—Fast, Small, and Under Control. Assistant Professor Nuno Martins (ECE/ISR) is the principal investigator. Co-PIs are Associate Professor Pamela Abshire (ECE/ISR), Associate Professor Elisabeth Smela (ME), and Assistant Professor Sarah Bergbreiter (ME/ISR). No robots at the sub-cm3 scale exist because their development faces a number of open challenges. This research will identify and determine means for solving these challenges. In addition, it will provide new solutions to outstanding questions about resource-constrained algorithms, architectures, and actuators that can be widely leveraged in other applications. The team will discover new fundamental principles, design methods, and technologies for realizing distributed networks of sub-cm3, ant-sized mobile microrobots that self-organize into cooperative configurations.
Figure-Ground Processing, Saliency and Guided Attention for Analysis of Large Natural Scenes
Professor Shihab Shamma (ECE/ISR) will contribute to an Office of Naval Research (ONR) MURI, "Figure-Ground Processing, Saliency and Guided Attention for Analysis of Large Natural Scenes." Maryland's portion of the award is $1.3 million. This award was made in MURI category 5: Bio-inspired Autonomous Agile Sensing and Exploitation of Regions of Interest within Wide Complex Scenes. The research will advance the computational architecture of sensors in large acquisition systems so that surveillance tasks in large natural scenes with complex imagery can be better accomplished. Shamma's contribution will be to define regions of interest both spatially and perceptually; to describe how visual and auditory search on the perceptual objects is guided by bottom-up saliency and by top-down knowledge of target features; to to search among these potential targets with a specific goal in mind; and to transfer the knowledge obtained from the neurophysiology, perceptual psychophysics and neural modeling into algorithms and architectures for solving problems of relevance.
Interior-Point Algorithms for Optimization Problems with Many Constraints
Professor AndréTits (ECE/ISR) is the co-principal investigator for a new Department of Energy (DoE) grant, “Interior-Point Algorithms for Optimization Problems with Many Constraints.” The Principal Investigator for this grant is Professor Dianne O’Leary (CS/UMIACS). The three-year, $303,701 grant continues the research of an earlier grant in the same area. The researchers will develop, analyze, and test algorithms for the solution of optimization problems with a very large number of inequality constraints, specifically, many more inequality constraints than variables.
Quantifying and Assuring Information Transfer in Dynamic Heterogeneous Wireless Networks
ISR-affiliated Professor Christopher Davis (ECE) and Civil Engineering Research Professor Stuart Milner have been awarded a three-year grant worth $1,048,279 from the Air Force Office of Scientific Research (AFOSR). The grant will support "Quantifying and Assuring Information Transfer in Dynamic Heterogeneous Wireless Networks." Milner will serve as the Principal Investigator (PI) while Davis will serve as Co-PI. The research will focus on network architectures and protocols that support information transfer. The researchers will address information-centric topology management and control vis-à-vis network topology management and control, with the intent of providing new analytical and mathematical tools to understand the factors affecting communications in complex wireless networks and their effect on network performance.
Advanced speech enhancement software
Professor Carol Espy-Wilson (ECE/ISR) is working with Baltimore-based Juxtopia LLC on a $168,960 grant to develop advanced speech enhancement software for Juxtopia's augmented reality products that need speech recognition to work in noisy environments.
Image Guided Autonomous Optical Manipulation of Cell Groups
Professor S.K. Gupta (ME/ISR) is the principal investigator for a three-year, $550K National Science Foundation grant, “Image Guided Autonomous Optical Manipulation of Cell Groups.” Associate Professor Wolfgang Losert (Physics) is the co-PI. The research team will create a computational foundation, methods, and tools for efficient and autonomous optical micromanipulation using microsphere ensembles as grippers. This system will make use of a holographic optical tweezer, which uses multiple focused optical traps to position microspheres in three-dimensional space.
Hand-held disagnostic instrument
Associate Professor Pamela Abshire (ECE/ISR) is partnering with the Rockville-based company Innovative Biosensors Inc. on a $235,596 grant to develop a hand-held diagnostic instrument for Group B Streptococcus, a type of bacteria that causes illness in newborn babies, pregnant women and the elderly. The device will enable rapid, automated detection for clinicians at the point of care.
Next-Generation Model Checking and Abstract Interpretation with a Focus on Embedded Control and Systems Biology
Professor Rance Cleaveland (CS/ISR) is the principal investigator and Professor Steve Marcus (ECE/ISR) is a co-PI for the University of Maryland’s portion of a major new National Science Foundation collaborative research grant, “Next-Generation Model Checking and Abstract Interpretation with a Focus on Embedded Control and Systems Biology.” The five-year, $10 million project is part of NSF’s “Expeditions in Computing” initiative. Maryland’s part of the project is worth $1.8 million. Along with Marcus, Tongtong Wu of the University of Maryland’s School of Public Health is also a co-PI. The consortium will develop new computational tools to help scientists and engineers analyze and understand the behavior of the complex models they develop for application domains ranging from systems biology to embedded control. Building on the success of model checking and abstract interpretation (MCAI), two well-established methods for automatically verifying properties of digital circuit designs and embedded software, this research project will extend the MCAI paradigm to systems with complex continuous dynamics and probabilistic behaviors. The research will include: understanding the precursors and course of pancreatic cancer; predicting the onset of atrial fibrillation; and obtaining deep design-time insights into the behavior of automotive and aerospace control systems. Ultimately, the project is expected to provide vital tools that will enable health care researchers to discover better treatments for disease and will allow engineers to build safer aircraft and other complex systems.
Theories and algorithms to perform non-intrusive forensic analysis on multimedia devices and digital content
ISR-affiliated Associate Professor Min Wu (ECE/UMIACS) is the co-PI for a three-year grant from the Air Force Office of Scientific Research (AFOSR) for theories and algorithms to perform non-intrusive forensic analysis on multimedia devices and digital content. Former ISR faculty member K.J. Ray Liu is the principal investigator (PI). The goal is to develop a holistic forensic framework to gather traces of evidence and answer who has done what, when, where, and how.
Predictors of Speech Quality after Tongue Cancer Surgery
Professor Carol Espy-Wilson is a co-PI for an NIH grant from the National Cancer Institute's Division of Cancer Control and Population Sciences (DCCPS) for "Predictors of Speech Quality after Tongue Cancer Surgery." Prof. Espy-Wilson's portion of the five-year, $2.8 million grant is $422,761. Tongue cancer surgery is a life saving procedure, but it typically leaves patients physically and mentally damaged, with speech communication difficulties that are in play every day. This research will improve the speech outcome of tongue cancer surgery by minimizing the impact of the tongue reconstruction and understanding the contributions of patient and surgical factors, so patients can communicate more clearly and confidently. Espy-Wilson will develop 3-D vocal tract models based on cine-MRI data to perform acoustic analysis of patients' speech signals to understand the effects of the tongue surgery on speech quality. The ultimate goal is to develop a procedure to help surgeons choose the best placement of a flap of tissue that is taken from elsewhere in the body to replace the removed cancerous tissue to maximize patients' speech quality.
Binary Rewriting without Relocation Information
Associate Professor Rajeev Barua (ECE/ISR) has been given a three-year, $350K NSF CSR grant, Binary rewriting without relocation information. This project focuses on the development of a new binary rewriter that can be use to statically transform binary code that does not have relocation information and to do so without the overhead of dynamic binary rewriting. The project will build a binary rewriting infrastructure that can rewrite binaries that do not contain relocation information.
Cooperative Networking across the Layers
Professor Tony Ephremides is the principal investigator (PI) on an NSF grant, "Cooperative Networking Across the Layers." The three-year, $371,166 grant is part of a larger collaborative project. The research will go beyond the physical layer in defining and analyzing cooperative techniques for wireless networks. By incorporating higher layer properties such as traffic dynamics and access control Ephremides and his fellow researchers will develop a new theoretical framework for analyzing and designing cooperative networking algorithms across the layers.
Discovering Designer Intent through Dynamic Analysis of Malware
Associate Professor Michel Cukier (ME/ISR) has been given a two-year, $150K NSF Trustworthy Computing grant, Discovering Designer Intent through Dynamic Analysis of Malware. The research addresses the problem of identifying and providing source code-based understanding of obfuscated malcode plaguing the Internet. Obfuscated malcode presents a clear and present danger to today's society in terms of individual privacy, security as well as to the Internet's overall trustworthiness. Attackers continue to use obfuscation to successfully defeat attempts by defenders to prevent infection or spread of the malcode. The goal of the research will be to develop dynamic binary analysis processes for Internet worm executables.
Adaptive Environment for Supercompiling with Optimized Parallelism (AESOP)
Associate Professor Rajeev Barua (ECE/ISR) is the PI and Professor Rance Cleaveland (CS/ISR) is a co-PI for a DARPA research grant, Adaptive Environment for Supercompiling with Optimized Parallelism (AESOP). The University of Maryland will collaborate with BAE Systems Inc and Princeton University on this four-year, $11.5 million program; Maryland’s share is $2.53 million. Reflecting the belief that serial programs will continue to represent the vast majority of programs in the world, AESOP will develop a state-of-the-art compiler that can automatically compile serial programs into parallel programs to a wide variety of platforms. Unlike existing efforts which have focused on regular, scientific programs alone, the AESOP project will use an aggressive suite of existing methods and new techniques that the researchers have developed to extract large-amounts of scalable parallelism even from seemingly serial irregular programs. This will enable software to exploit the full potential of the hardware in the modern multi-core era. Further, the compiler will accurately characterize and compile to a wide variety of computer systems without any manual effort.
Particle Filtering for Stochastic Control and Global Optimization
Professor Steve Marcus (ECE/ISR) and Professor Michael Fu (BMGT/ISR) are co-PIs for a three-year, $390K NSF grant, Particle Filtering for Stochastic Control and Global Optimization. The objective of this program is to provide new breakthroughs in the areas of stochastic control and global optimization through insights gained from particle filtering and from additional recent results in nonlinear filtering. Stochastic control and optimization can be applied to many problems of critical concern in US industry, so the resulting algorithms will have broad and transformative applicability. In the project, they will be tested on problems in industries from telecommunications to manufacturing to finance.
Nanofabrication Using Viral Biotemplates for MEMS Applications
Professor Reza Ghodssi (ECE/ISR) is the PI for a three-year, $401,712 NSF grant, "Nanofabrication Using Viral Biotemplates for MicroElectroMechanical Systems (MEMS) Applications." The research will make use of the self-assembly and metal-binding properties of a biological nanostructure, the Tobacco Mosaic Virus (TMV), in the development of novel functional materials and fabrication processes for energy microsystems applications. The TMV is a high aspect ratio cylindrical plant virus that can be genetically engineered to include amino acids with enhanced metal-binding properties. These genetic modifications facilitate electroless plating of the molecules as well as self-assembly onto various substrates. The developed processes will be incorporated in the fabrication of new, nanostructured small-scale energy storage devices.
NSF RI: Extension of the APP detector for multipitch tracking and speaker separation
In many real world scenarios, speech recognition and speaker identification systems must deal with simultaneous speech from several talkers, i.e., speech mixtures representing conversations in natural environments. Users of cochlear implants encounter problems in separating speakers in multi-speaker environments, because of the loss of fine temporal structure. Thus, a crucial preprocessing step for such systems is the segregation of speech according to its constituent sources. The project is the first part of this process which involves the recognition of the number of speakers and the separation of their pitch tracks based on the periodic portions of the speech signal (i.e., voiced regions). Since different speakers have characteristic pitch ranges as a consequence of vocal cord physiology, pitch tracks can be used to help separate the combined signal into different speech streams. Current popular multi-pitch tracking approaches are susceptible to artifacts caused by the interaction between the periodic regions of the different speech signals. Consequently, the periodicity of the combined signal can be different from that of the individual components. The major new idea is the extension of an existent periodicity and pitch estimation process to higher dimensions, arriving at a multi-dimensional periodicity function which is not susceptible to the harmonic interaction artifacts. Preliminary results show that the multiple pitch tracks obtained are accurate even when one speaker is considerably more dominant than the other speaker. The approach is easily generalized to non-speech audio and it should be robust in noisy channels. The outcome of this project will be used in a future project where the actual speech streams will be separated from each other based on the multi-pitch information.
Extension of the APP detector for multipitch tracking and speaker separation is a two-year, $125K grant.
NSF: Nonlinear Signal Processing and Wireless Communications using Frames and Operators Theory
This research will develop a new mathematical framework for nonlinear signal processing and wireless communication channels.
The nonlinear signal processing problem addressed here is signal reconstruction from the magnitude of a redundant linear representation. When the linear redundant representation is associated to a group representation (such as the Weyl-Heisenberg group), the relevant Hilbert-Schmidt operators inherit this invariance property. Thus a fast (nonlinear) reconstruction algorithm seems possible. A wireless communication channel is modeled as a linear operator that describes how transmitted signals propagate to a receiver. For ultrawide band (UWB) signals, the Doppler effect no longer can be modeled as a frequency shift. Instead it is captured as a time dilation operator. A continuous superposition of time-scale shifts is used to model a UWB communication channel, and consequences to pseudo-differential operator theory are analyzed.
The investigator takes up two problems related to signal processing. In the first he considers how to represent signals in ways that allow more effective reconstructon of them from limited information. In the second he analyzes properties of wireless communication channels, aiming at improvements in transmission. The solutions to these problems have a strong impact in the strategic area of information technology. Important applications such as signal processing, X-ray crystallography, and quantum computing are affected by solutions to the first problem. High-impact applications related to the second problem include ultrawide-band through-wall imaging systems, higher-throughput 802.15 Wireless Personal Area Networks, and wireless sensor networks.
Nonlinear Signal Processing and Wireless Communications using Frames and Operators Theory is a four-year, $177K grant.
NSF: Collaborative Research: Coding for Nano-Devices, Flash Memories, and VLSI Circuits
Specifically, the research carried out in this project can be roughly subdivided into the following four focus areas:
-- Development of new coding schemes for efficient addressing and correction of manufacturing defects in next-generation memory nano-devices, in particular the nano-wire crossbar.
-- Advanced coding techniques for high-density flash memories, based upon ground-breaking recent ideas of floating codes and rank-modulation coding.
-- Development of coding schemes to reduce power dissipation and to avoid cross-talk in VLSI circiuts, with particular emphasis on both on-chip and off-chip buses.
-- Applications to circuit design of the techniques developed in a range of well-known combinatorial problems in coding theory, including covering arrays, separating codes, intersecting codes, and qualitatively independent set families.
Collaborative Research: Coding for Nano-Devices, Flash Memories, and VLSI Circuits is a four-year, $300K grant.
NSF Collaborative Research: Multivariate positive definite polynomials and their applications via SDP
This project is devoted to the study of point allocations on the real sphere and related configurations using methods of distance geometry, coding theory, and semidefinite programming. The properties of the point sets studied include restricting the minimum angular separation between any pair of distinct points in the set or the degree of the cubature formula supported by it. Recent advances in these problems include a solution by the investigator of the kissing number problem in 4 dimensions, a new proof for the kissing number problem in 3 dimensions, and a new approach to bounds on codes using semidefinite programming, due to Schrijver, Bachoc, and the investigator. The kissing problem in x dimensions is the question of how many unit spheres can touch (kiss) a unit sphere in x dimensions. The new ideas developed in these works pave the way for further advances in the problems of bounding the size of codes and in a number of other problems in distance geometry. The main problems to be addressed in the project are related to bounding the size of optimal sets of points on a sphere when the sets have a certain property, and the links between the bounding problem and multivariate positive definite polynomials. Interesting properties of the point set include having a minimum angular separation that exceeds a given value between any two points in the set (this is relevant for signal processing problems), and supporting an exact cubature formula for spherical harmonic functions of a given degree. Applications of the point sets studied include communication theory, numerical analysis, the meshing problem, data representation, and localization in sensor networks.
Multivariate positive definite polynomials and their applications via SDP is a thre-year, $114K grant.
NSF: An AUV Manipulator/Vision System for Autonomous Interventions
This research will develop an autonomous system for remote sampling of biological and geological specimens from the sea floor using a robotic manipulator mounted on an autonomous underwater vehicle (AUV). Visual sensing from a stereoscopic camera system called AVATAR will be integrated with the control system for the SAMURAI underwater manipulator to produce a robust autonomous sampling system. In addition, a front-end graphical user command interface will be integrated to the system to allow real-time designation of targets for autonomous sampling or other dexterous manipulation from remotely operated vehicles (ROV) and manned submersibles.
The utility of this advanced autonomous sampling system will be demonstrated by teaming with investigators at the Woods Hole Oceanographic Institution by conducting operational sampling tasks of specimens in sea trials off the coast of Cape Cod and on an Atlantic scientific cruise. The SAMURAI/AVATAR system will provide marine scientists with the capability of autonomous or teleoperated interventional tasks from any hovering undersea vehicle.
An AUV Manipulator/Vision System for Autonomous Interventions is a three-year, $481K grant.
NSF: Addressing Physical-Layer Challenges via CLAWS: Cross-Layer Approaches to Wireless Secure Communications
Wu will investigate new approaches to achieving security in wireless communications systems and other complex networks using physical layer properties. The Cross-Layer Approaches to Wireless Secure Communications (CLAWS) effort aims to address security in new communication paradigms where security is difficult to provide only through existing cryptographic and network security techniques. The CLAWS approach attempts to jointly optimize overall system performance and security. The scheme should be applicable to wireless sensor networks, wireless ad-hoc networks, and future-generation wireless and hybrid communication systems.
Addressing Physical-Layer Challenges via CLAWS: Cross-Layer Approaches to Wireless Secure Communications is a four-year, $312K grant.
NSF: Simulating the Dynamics of Electrowetting: Modeling, Numerics, and Validation
Electrowetting is a technique for manipulating fluids on the micro-scale. By applying voltages at actuating electrodes, it is possible to (effectively) modify surface tension properties, and to move, split, merge, and mix liquid packets. Applications of electrowetting include re-programmable lab-on-a-chip systems, auto-focus cell phone lenses, and colored oil pixels for laptops and video-speed smart paper.
The PIs will develop experimentally validated models that will predict electrowetting dynamics first in two, then in three, spatial dimensions, which will enable next-generation system analysis, design, and control. The models will include the essential bulk-flow physics: surface tension, low-Reynolds fluid dynamics, electrostatics or electrodynamics, as well as critical loss-phenomena such as contact angle saturation and hysteresis.
Simulating the Dynamics of Electrowetting: Modeling, Numerics, and Validation is a four-year, $310K grant.
NSF CSR-PSCE,SM: Compiler-Directed System Optimization of a Highly-Parallel Fine-Grained Chip Multiprocessor
Accelerating single programs on multicore processors remains an outstanding challenge in computer systems design. Unfortunately, existing parallel systems achieve little speedup on programs other than regular dense-matrix codes. And, most of the world's programs are in this category, broadly termed non-regular code. Of course some non-regular codes have little parallelism beyond instruction level parallelism (ILP); hence no speedup is possible on multicores. However in other non-regular code, parallelism is present but is not exploitable. Reasons include high synchronization costs, non-loop parallelism, non-array data structures, recursively expressed parallelism and parallelism that is too fine-grained to be exploitable.
This project is developing new compiler technologies for XMT to achieve scalable performance in the face of architecture decisions made for scalability. It is studying better compiler techniques to achieve scalable performance for UMA architectures such as XMT.
CSR-PSCE,SM: Compiler-Directed System Optimization of a Highly-Parallel Fine-Grained Chip Multiprocessor is a four-year, $400,000 grant.
NSF: Cell-Based Olfactory Sensing for Biometrics
The gold standard against which chemical sensors are compared is the dog's nose. However, dogs are expensive to train and can only be used a few hours per day. By detecting the electrical signals produced by olfactory sensory neurons (OSNs), it should be possible to achieve high-sensitivity, high-specificity, high-speed, stand-off detection of trace amounts of compounds associated with volatile human compounds characteristic of gender, stress, individual "fingerprint," and various medical conditions. The team plans to develop a miniaturized system for human biometric characterization using, initially immortalized cell lines for detection of human compounds and then developing techniques for direct detection of airborne odorants using artificial mucous, thin membranes, continuous perfusion with water or a combination. Cell-based chemical sensors will have broad societal benefits through diverse applications, outside of biometric detection: explosives detection, monitoring food and air, odor-based medical diagnosis, drug detection in airports, and screening of pharmaceuticals, to name a few.
Cell-Based Olfactory Sensing for Biometrics is a six-year, $391K grant.
NSF: Photoelectrochemical Films for Solar H2 Production: A Combinatorial CVD Approach
Since the original demonstration of photo-assisted water electrolysis by Fujishima and Honda in 1972, tremendous effort has gone into developing photoelectrochemical (PEC) materials and systems. Numerous research programs have focused on improving the efficiency of these devices, and of those that have been successful, few have addressed the issue of whether such devices would be practical or environmentally desirable to manufacture on the scale necessary to impact the US's energy requirements.
The PIs plan to develop new semiconductor materials and solar cell devices for the production of hydrogen by the PEC decomposition of water with a manufacturing and product lifecycle perspective. The PEC materials development program builds directly on the complementary skills of the project PIs: the Adomaitis group's combinatorial chemical vapor deposition (CVD) reactor designs for material property and manufacturability optimization, and the Ehrman group's expertise in developing nanostructured films of doped copper oxide for PEC applications by flame synthesis and other manufacturing techniques.
The outcomes of this research program have the potential to broadly impact green manufacturing and energy production technologies.
Photoelectrochemical Films for Solar H2 Production: A Combinatorial CVD Approach is a four-year, $325K grant.
Towards Modeling Mobile Wireless Networks—When Connectivity Meets Mobility
Professor Armand Makowski (ECE/ISR) is the principal investigator, and Associate Professor Richard La (ECE/ISR) is the co-PI for a new National Science Foundation grant, Towards Modeling Mobile Wireless Networks—When Connectivity Meets Mobility. The three-year, $260K grant will explore how different notions of network connectivity shape resource allocation in the presence of node mobility. The researchers will explore how different notions of network connectivity shape resource allocation (e.g., energy) in the presence of node mobility.
NSF SGER: Integrated Indium Phosphide Based Microsystem for Chemical Sensing
This research explores the possibility of optical detection of chemicals using an integrated system on an indium phosphide substrate. It will include a laser source, integrated directly with a microcantilever and photodetectors, that will permit the precise tracking of the resonant frequency of the cantilever. Functionalized coatings on the cantilever will be used to absorb chemicals from the environment and this interaction will change the mass, and consequently, the resonant frequency, of the cantilever. The system implementation will include a servo-control circuit. The integration of a micromechanical and photonic system is expected to yield very high sensitivity.
Integrated Indium Phosphide Based Microsystem for Chemical Sensing is a one-year, $60K grant.
High-Performance Simulations and Interactive Visualization for Automated Nanoscale Assembly
Professor S.K. Gupta (ME/ISR) is the principal investigator for a new National Science Foundation CDI-Type 1 grant, High-Performance Simulations and Interactive Visualization for Automated Nanoscale Assembly. The three-year, $550K grant will develop a fundamental understanding of the interaction of nanocomponents with trapping fields. Amitabh Varshney (CS) is the co-PI. The research will lead to a reliable, efficient, and automated assembly process for fabricating nanocomponent-based devices. This assembly process will enable nanotechnology researchers to explore new design possibilities in nano electronics, nano photonics, and bio-inspired sensors.
NSF CMMI: Mechanical Phenotyping of Cells: Haptics-Enabled Atomic Force Microscopy
The research objective of this award is to investigate novel approaches for using Atomic Force Microscopy (AFM), combined with haptic (sense of touch) feedback, to mechanically phenotype and monitor individual cells. To enable this, one of the primary tasks in this project will be to develop a magnetically levitated haptic feedback device with near zero friction and sufficient fidelity so that a user can ?feel? individual cells. Furthermore, in the AFM studies, we will monitor the stiffness of the different cell types for both local and global responses. For global stiffness measurements, we will use modified AFM cantilevers whereby the diameter of the ball at the tip will be significantly larger than that of the cell. We will use localized measurements to understand the variation in the stiffness at various locations on the cell surface for each type of cell. We will use the Hertz contact model to quantify the mechanical response of the cell for local and global cell probing tasks. Such studies will help us to create a database of the mechanical properties of the cells. Combing haptic feedback with the AFM and understanding the effectiveness of the haptic device in mechanically phenotyping cells is the end-goal of this project.
This research will lead to the development of improved methods of targeting embryonic stem cell differentiation for diagnostic and therapeutic purposes and monitoring cellular responses to environmental stimuli.
Mechanical Phenotyping of Cells: Haptics-Enabled Atomic Force Microscopy is a four-year, $215K grant.
Common Randomness, Multiuser Secrecy and Tree Packing
Professor Prakash Narayan (ECE/ISR) is the principal investigator for a new National Science Foundation grant, Common Randomness, Multiuser Secrecy and Tree Packing. The three-year, $400K grant will take a multiuser information theoretic approach to investigate innate theoretical connections that exist between multiuser source and channel coding, information theoretic network security, and combinatorial tree packing algorithms in theoretical computer science.
NSF: Verification of Open-Loop Embedded Control Systems
This project develops automated techniques for efficiently analyzing the correctness of open-loop embedded control software. Such software is widespread in the real-world, in automotive, flight-control, medical-device and other human-in-the-loop applications, where environmental behavior is unpredictable. The research effort is based on the observation that such software can be effectively modeled using a particular mathematical formalism called timed automata. The specific topics being studied include: 1) Model checking: novel on-the-fly algorithms, in which system behavior is explored in a demand-driven manner, are being developed for checking properties of timed automata. 2) Industry-standard modeling and model checking: strategies are being devised for adapting the model-checking tools to industry-standard modeling notations such as Simulink© and for exploiting model structure to enable verification of large models that arise in practice. The significance and impact of the work derive from the more thorough verification of control software the new technologies will enable. By automating formal validation activities and supporting widely used modeling tools, the research will empower engineers to conduct more intensive analyses of their control-system designs earlier in the life-cycle than current techniques allow.
Verification of Open-Loop Embedded Control Systems is a four-year, $350K grant.
NSF: EXP-LA: Olfactory Receptor Cell-Based Detection of Explosives
The objective of this research project is to develop a miniaturized system for detecting explosives based on odorant sensing using mammalian olfactory sensory neurons (OSNs). This will be achieved by fabricating an integrated microsystem on which OSNs are cultured and monitored. By detecting the electrical signals produced by OSNs, it would be possible to achieve high-sensitivity, high-specificity, high-speed, stand-off detection of trace amounts of compounds present in explosives.
EXP-LA: Olfactory Receptor Cell-Based Detection of Explosives is a four-year, $800K grant.
NSF CSR-EHS: Memory management as a run-time service
This research is developing a SPM allocation strategy that is completely implemented inside a binary rewriter. This binary rewriter is called automatically by the operating system the first time the program is loaded to memory. Subsequent executions derive the benefits of SPM with no additional overhead. This approach makes SPM a run-time-provided resource for the first time, much like cache and virtual memory are, making it ubiquitous and transparent to the software toolchain.
CSR-EHS: Memory management as a run-time service is a four-year, $180K grant.
NSF Optimal Reference Tracking, the Next Step in the Design of Controllers for Markovian Jump Linear Systems
The research develops the first collection of methods, for designing controllers that achieve optimal reference tracking, for randomly time-varying systems. As a first step, the PI adopts a Markovian jump linear system formulation because it retains the tractability of the linear deterministic case, while featuring a stochastic variation of its underlying structure. Recent results provide solutions to the H2 and H_inf optimal regulator (no reference) problems, for Markovian jump linear systems. However, the paradigm described in this proposal, where a reference has to be tracked, has not been investigated and it cannot be addressed by methods based on classical adaptations of optimal regulation theory, such as the internal model principle. The PI expects that an efficient design methodology will rely on a new framework for the joint design of the state-estimator, the state-feedback controller and the feedforward terms, using linear matrix inequality techniques. The research will also unveil structural properties of servomechanisms that achieve optimal reference tracking, in the presence of random or intermittent failures.
Optimal Reference Tracking, the Next Step in the Design of Controllers for Markovian Jump Linear Systems is a two-year, $97K grant.
NSF CompBio: Reality-based Data-driven Computer Models for Surgical Simulation
The proposed research will make fundamental advances in our ability to simulate and reason about soft-tissue interactions accurately, and will lead to several exciting scientific and clinical possibilities. Scientifically, we will be able to develop accurate and reality-based soft-tissue models based on actual experimental trials, which have wide application in medicine. Optimized numerical algorithms can then build on these accurate nonlinear material and contact interaction models for real-time graphical and haptic force-feedback display of soft tissues. Clinically, this will allow a more widespread use of surgical simulators for resident training (for both minimally invasive and direct procedures), whereby residents will be able to experience more realistic soft-tissue interaction response in surgical tasks. Advancement in this area will also open avenues for modeling any other organ or soft-tissue for which training is desired, after the core reality-based simulation issues are resolved.
CompBio: Reality-based Data-driven Computer Models for Surgical Simulation is a five-year, $275K grant.
NSF NeTS-NOSS: The BehaviorScope Project: Sensory Grammars for Sensor Networks
The BehaviorScope project seeks to develop a framework for understanding patterns and behaviors from sensor data and metadata in distributed multimodal sensor nodes. Patterns and behaviors (especially of humans) will be parsed by a hierarchy of probabilistic grammars and other mechanisms into a compact and more descriptive semantic form. These higher-level interpretations of the data will provide the necessary network cognition needed to provide services in many everyday life applications such as assisted living, workplace safety, security, entertainment and more. The project will use a lightweight camera sensor network as its primary platform and will focus on two types of spatio-temporal data processing. At the local sensor's field of view, this research will investigate the design of filters for robustly detecting humans as well as their gestures and postures. At a more macroscopic level, collections of sensors will coordinate to detect longer term patterns of behavior. The expected outcome is a new data interpretation framework that can understand the spatial and temporal aspects of data and respond to them with meaningful services. To collect real data and to demonstrate the developed concepts in practical applications, this work will use assisted living as the driver application. In this context, the developed sensor network will supervise the behaviors of elders living alone at home to generate daily activity summaries, post warnings and alarms when they engage in dangerous activities, and provide a variety of services that increase the autonomy and independence of these individuals.
The BehaviorScope Project: Sensory Grammars for Sensor Networks is a two-year, $150K grant.
NSF: Transceiver and Network Technology Developments for Directional Hybrid Wireless Networks
Mobile ad-hoc networks (MANETs) do not scale. The aim of this research is to prove that a higher communication tier can be created using autonomously configuring directional links in a flexible backbone network that connects MANET-like small clusters in an architecture that is "base-station-like." This research will address important, unsolved research problems in stabilization, pointing, acquisition, tracking (SPAT), bootstrapping, and topology control algorithms needed to make our "hybrid" directional free space optical (FSO) and radio frequency (RF) networks a reality. The research will help to resolve link physics issues that affect the FSO/RF channel, including: (i) fading of the urban hybrid FSO/RF channel; (ii) measurements of temporal and spatial correlation functions on the channel; and (iii) studies of the performance of non-imaging FSO receivers with regard to amelioration of the tip-tilt and beam break-up problems of the FSO channel. We will also build and study new optical wireless nodes with novel design features that make them potentially valuable in indoor optical wireless applications where RF is not desirable because of interference problems, such as in the healthcare industry.
Transceiver and Network Technology Developments for Directional Hybrid Wireless Networks is a three-year, $320K grant.
NSF CAREER: Biology-Inspired Miniature Optical Directional Microphones: Bridging Biological Systems and Sensor Technology
This NSF CAREER Award research will transfer biology-inspired ideas into smart, small-scale sensors, and to educate future generations of students and researchers with multi-disciplinary perspectives. Inspired by the micro-scale ears of the fly Ormia, which show remarkable sound localization ability, the research plan is to develop a new class of miniature directional microphones. This entails a new approach for sensor development via the integration of biology-inspired solutions, mechanics modeling, micro-fabrication techniques, and optical detection strategies. The mechanics model will help unravel the underlying science of the fly's hearing mechanism and develop sensor design guidelines. The low coherence interferometer based optical system will overcome the limit of state-of-the-art detection techniques. This new bio-inspired sensing paradigm for sound localization is expected to have a significant impact in areas such as health care, safety, and defense.
Biology-Inspired Miniature Optical Directional Microphones: Bridging Biological Systems and Sensor Technology is a five-year, $400K grant.
NSF Collaborative Research CT-ISG: Secure Capacity of Wireless Networks
This project takes an information theoretic approach to provide guarantees on information security and information reliability for wireless networks. The research includes the development of a comprehensive wireless network design framework that aims at achieving high capacity and secure transmission for all users.
Secure Capacity of Wireless Networks is a three-year, $125K grant.
NSF Collaborative Research: Automatic Generation of Context-Dependent Simplified Models to Support Interactive Virtual Assembly
The objective of this award is to develop a mathematical theory and computational framework for the automatic generation of context-dependent simplified models to support interactive virtual assembly applications. Interactive virtual assembly is emerging as an important tool for evaluating ease-of assembly of proposed products, and training assembly operators. With the advent of low cost personal virtual environments, interactive virtual assembly holds the promise of replacing expensive, and time consuming, physical prototyping and training. However, real-time interactions in low-cost virtual environments can only be achieved through judicious model simplification. Through a fundamental understanding of the interplay between model simplification, computational speed and accuracy, a framework will be developed for optimizing model simplification for virtual assembly.
This research will enable interactive virtual assembly with provable performance guarantee on low cost personal virtual environment, leading to a significant increase in the use of virtual assembly technology in design and training applications.
Automatic Generation of Context-Dependent Simplified Models to Support Interactive Virtual Assembly is a five-year, $243K grant.
NSF RI Collaborative Research: Landmark-based Robust Speech Recognition Using Prosody-Guided Models of Speech Variability
The research will develop large-vocabulary psychologically realistic models of speech acoustics, pronunciation variability, prosody, and syntax by deriving knowledge representations that reflect those proposed for human speech production and speech perception, using machine learning techniques to adjust the parameters of all knowledge representations simultaneously in order to minimize the structural risk of the recognizer. The team will develop nonlinear acoustic landmark detectors and pattern classifiers that integrate auditory-based signal processing and acoustic phonetic processing, are invariant to noise, change in speaker characteristics and reverberation, and can be learned in a semi-supervised fashion from labeled and unlabeled data. In addition, they will use variable frame rate analysis, which will allow for multi-resolution analysis, as well as implement lexical access based on gesture, using a variety of training data.
The work will improve communication and collaboration between people and machines and also improve understanding of how human produce and perceive speech
Landmark-based Robust Speech Recognition Using Prosody-Guided Models of Speech Variability is a six-year, $542K grant.
NSF CAREER: Distributed control of dynamic systems using a wireless communcation medium: two new paradigms
This NSF CAREER award introduces two new paradigms. The first paradigm, denoted as networked preview control, specifies a framework consisting of a wireless network of spatially-distributed sensors and one controller. Given a disturbance field, networked preview control aims at using the remote sensors to provide the controller with disturbance preview information. The second paradigm concerns the design of cooperative control strategies for a mix of mobile and static agents, with the objective of attaining pre-specified communication objectives.
Distributed control of dynamic systems using a wireless communcation medium: two new paradigms is a five-year, $412K grant.
NSF III-COR: iOPENER - A Flexible Framework to Support Rapid Learning in Unfamiliar Research Domains
The goal of iOPENER (Information Organization for PENning Expositions on Research) is to generate readily-consumable surveys of different scientific domains and topics, targeted to different audiences and levels, e.g., expert specialists, scientists from related disciplines, educators, students, government decision makers, and citizens including minorities and underrepresented groups. Surveyed material is presented in different modalities, e.g., an enumerated list of articles, a bulleted list of key facts, a textual summary, or a visual presentation with zoom and filter capabilities.
III-COR: iOPENER - A Flexible Framework to Support Rapid Learning in Unfamiliar Research Domains is a four-year, $720K grant.
NSF: Correlation, Cooperation and Feedback (CCF) in Multi-user Wireless Communications
This research will develop a fundamental understanding and a comprehensive theory for optimum distributed coding, transmission, creation and exploitation of correlation in multi-user wireless networks. In order to achieve this goal, the investigator will distill the main theoretical challenges, initially isolate and tackle them in smaller sub-problems, and then finally integrate them to develop a unified theory.
Correlation, Cooperation and Feedback (CCF) in Multi-user Wireless Communications is a four-year, $350K award.
NSF Collaborative Research: Systematic Optimization in Wireless Multicasting
In this research, investigators will model a wireless ad hoc network by means of a topology graph, which contains point-to-point links and point-to-multipoint hyperarc links with coupled link throughput capacities. Under the assumption of optimal network coding, the research first develops an iterative gradient-steering" optimization framework. A network utility maximization problem is converted to a transmission scheduling problem that maximizes an approximated utility in its gradient direction, coupled with a steering vector update that continuously updates the approximated utility and its instantaneous gradient direction. The research then extends the framework to utility maximization for a network with multiple multicast sessions. Finally, the research develops distributed algorithms to optimize a global utility of a large scale network using local controllers. In addition to the planned research, the investigators will also try to extend the algorithm to ad hoc networks with time varying channels where utility maximization requires efficient exploitation of the channel diversity gain.
Systematic Optimization in Wireless Multicasting is a four-year, $234K grant.
NSF: Modeling Wireless Networks: Excursions in the Theory of Random Graphs
The research investigates three classes of random graph models, namely random connection graphs, random intersection graphs and a combination thereof known as Kryptographs. Both the models and research questions are driven by applications from the fields of wireless networking and sensor network security.
Modeling Wireless Networks: Excursions in the Theory of Random Graphs is a four-year, $226K award.
NSF: Optimization Schemes for Large Scale Digital Circuits in Presence of Fabrication Randomness
Reduction in fabrication dimensions has resulted in significant increase in the randomness associated with the fabricated parameters of large scale digital circuits. This has begun to severely impact the manufacturing yield and therefore the profitability of the semiconductor industry. In this research the investigators are focusing on developing formal optimization schemes for synthesizing large scale digital circuits while proactively considering randomness induced yield loss as an optimization criteria.
Optimization Schemes for Large Scale Digital Circuits in Presence of Fabrication Randomness is a four-year, $150K grant.
ASEE Summer Faculty Fellowship Award
Fundamental Advances in Control of Wireless Sensor and Robotic Networks
Assistant Professor Nikhil Chopra (ME/ISR) is the principal investigator for a three-year, $300K National Science Foundation grant, “Fundamental Advances in Control of Wireless Sensor and Robotic Networks”. Chopra will investigate fundamental issues in network control and distributed coordination of wireless sensor and robotic networks. This research has the potential to lead to a transformational change in understanding the mechanisms for delay instability and spatio-temporal synchronization in cyber-physical systems. Such understanding will help in solving delay-instability, synchronization, and coordination problems in wireless sensor and robotic networks without sacrificing the performance, scalability, or modularity of the system.