Abstract

The dramatic increases in demands from multimedia applications are putting an enormous strain on current cellular system infrastructure. Hence, we are witnessing significant research and development efforts on 4G multi-channel wireless cellular systems (e.g., LTE and WiMax) that target new ways to achieve higher data rates, lower latencies, and a much better user experience. An important requirement for achieving these goals is to design efficient scheduling policies that can simultaneously provide high throughput and low delay. In these multi-channel systems, such as OFDM, the Transmission Time Interval (TTI), within which the scheduling decisions need to be made, is typically on the order of a few milliseconds. On the other hand, there are hundreds of orthogonal channels that can be allocated to different users. Hence, many decisions have to be made within a short scheduling cycle and it is critical that scheduling policies must be of low complexity. In this talk, we will present a unifying framework for designing low-complexity scheduling policies in the downlink of multi-channel (e.g., OFDM-based) wireless networks that can provide optimal performance in terms of both throughput and delay. We first develop new easy-to verify sufficient conditions for rate-function delay-optimality in the many-channel many-user asymptotic regime. and for throughput-optimality in non-asymptotic settings.

The sufficient conditions enable us to prove rate-function delay optimality for a class of Oldest Packets First (OPF) policies and throughput optimality for a large class of Maximum Weight in the Fluid limit (MWF) policies, respectively. While a recently developed scheduling policy is both throughput-optimal and rate-function delay-optimal, it has a very high complexity of O(n^5), where n is the number of channels or users, which makes it impractical. By intelligently combining policies from the classes of OPF policies and MWF policies, we design hybrid policies that have a low complexity of O(n^{2.5} log n), without losing either throughput-optimality or rate-function delay-optimality. We further develop two simpler greedy policies that are both throughput-optimal and have a positive rate-function. We show through simulations that empirically these simpler mechanisms have near-optimal value of rate-function in various scenarios. Finally, we propose a class of throughput-optimal policies with even lower complexity that allows an explicit trade-off between complexity and delay performance.

Biography

Ness Shroff received his Ph.D. degree in Electrical Engineering from Columbia University in 1994. He joined Purdue university immediately thereafter as an Assistant Professor in the school of ECE. At Purdue, he became Full Professor of ECE in 2003 and director of CWSA in 2004, a university-wide center on wireless systems and applications. In July 2007, he joined The Ohio State University, where he holds the Ohio Eminent Scholar endowed chair professorship in Networking and Communications, in the departments of ECE and CSE. Since 2009, he also serves as a Guest Chaired professor of Wireless Communications at Tsinghua University, Beijing, China. His research interests span the areas of communication, social, and cyberphysical networks. He is especially interested in fundamental problems in the design, control, performance, pricing, and security of these networks. Dr. Shroff is a past editor for IEEE/ACM Trans. on Networking and the IEEE Communication Letters. He currently serves on the editorial board of the Computer Networks Journal, IEEE Network Magazine, and the Networking Science journal. He has chaired various conferences and workshops, and co-organized workshops for the NSF to chart the future of communication networks. Dr. Shroff is a Fellow of the IEEE and an NSF CAREER awardee. He has received numerous best paper awards for his research, e.g., at IEEE INFOCOM 2008, IEEE INFOCOM 2006, IEEE IWQoS 2006, Journal of Communication and Networking 2005, Computer Networks 2003, and one of two runner-up papers at IEEE INFOCOM 2005.

Abstract:

Many scientifically important questions require the efficient use of high-performance and distributed computing in order to provide answers with the accuracy needed at the length and time-scales required. We begin by analyzing how and why it has been necessary to develop "effective abstractions" in order to successfully utilize production high-performance distributed cyber-infrastructure, such as NSF's TeraGrid/XSEDE. For example, pilot-jobs are arguably one of the most widely-used distributed computing abstractions, and have been shown to support scalable and dynamic utilization of distributed resource.

However, there does not exist a well-defined, unifying conceptual model of pilot-jobs which can be used to define, compare and reason across different implementations of pilot-jobs; this presents a barrier to extensibility and interoperability. We introduce the P* Model the first known conceptual model of pilot-jobs, validate its implementation via the Pilot-API -- by concurrently using multiple distinct pilot-job frameworks on distinct production distributed cyber-infrastructures, and propose extensions of the P* Model to data.

We will discuss the application of the pilot-abstraction to support the infrastructural and algorithmic requirements of several Grand Challenge problems facing the Computational Biology community, for example data-analytics for next-generation gene sequencing, enhanced sampling molecular algorithms, and in-silico personalized and predictive health-care.

For Graduate students looking for research opportunities, we will conclude by providing a brief overview of the Radical group and some research topics currently of interest.

Biography:

Prof. Shantenu Jha is an Assistant Professor at Rutgers University, a member of the Graduate Faculty in the School of Informatics at the University of Edinburgh (UK), and a Visiting Scientist at University College London. Before moving to Rutgers, he was the lead for Cyberinfrastructure Research and Development at the CCT at Louisiana State University. His research interests lie at the triple point of Computer Science, Cyberinfrastructure Development and Computational Science.

Shantenu is the lead investigator of the SAGA project ( http://www.saga-project.org), which is a community standard and is part of the official middleware/software stack of most major Production Distributed Cyberinfrastructure -- such as US NSF's XSEDE and the European Grid Infrastructure. His research has been funded by multiple NSF awards, US National Institute for Health (NIH) as well as the UK EPSRC (OMII-UK project and Research theme at the e-Science Institute). Jha is the author of approximately 60 publications; he has won some of the most prestigious awards in high-performance computing at ACM/IEEE Supercomputing and the International Supercomputing Series.

Abstract:

Pressure on financial models and time to market create a relationship between speed of computation and business success. This talk explains how the application of dataflow techniques by JP Morgan has achieved cutting edge performance, whilst also helping to improve trading strategy, decision making and risk management.

Biography:

Stephen is currently head of the Applied Analytics group within the investment banking division of JP Morgan. The group is responsible for accelerating mathematical models across asset classes for trading and risk management using dataflow computational techniques. Prior to joining JP Morgan Stephen spent lengthy periods at Deutsche Bank, Credit Suisse, Barclays and UBS. Prior to entering investment banking he also spent 5 years as a university lecturer teaching mathematical economics, banking, finance and monetary theory. Stephen holds a PhD in mathematical finance from Cass Business School in London.

Abstract

Wireless devices and sensors are increasingly ubiquitous in all aspects of life. As a result, researchers have worked tirelessly to provide more functionality and ever higher data rates to the devices. Researchers are challenged to use energy more efficiently, due to finite battery capacity and increasingly as everyone is asked to reduce their demands from the electric grid. In this talk I will address the challenge of using energy more efficiently in wireless communications systems by leveraging linearization around CMOS switching amplifiers. These switching amplifier topologies provide means to increase output power, efficiency and integratability of the PA with the rest of the radio circuitry, a major stumbling block in the quest for the RF system-on-a-chip (SOC).

I will summarize why switching amplifiers can outperform their linear counterparts and offer potential for tunability and reconfigurability for software defined radio (SDR) applications. Next I will motivate linearization methods that allow switching PAs to be used with non-constant envelope modulation, including pulse-width and -position modulation (PWPM) and envelope elimination and restoration (EER). The switched-capacitor PA, a topology that utilizes switched capacitors to enable a significant improvement in average efficiency and linearity utilizing a combination of data converter and power amplifier techniques will be introduced. It represents an exciting path towards SDR ready CMOS power amplifiers. I will conclude the talk with a few interesting research directions in energy efficient RF CMOS circuit design.

Biography

Dr. Walling received the B.S. degree from the University of South Florida, Tampa, in 2000, and the M.S. and Ph. D. degrees from the University of Washington, Seattle, in 2005 and 2008, respectively. Prior to starting his graduate education he was employed at Motorola, Plantation, FL working in cellular handset development. He interned for Intel, Hillsboro from 2006-2007, where he worked on highly-digital transmitter architectures and CMOS power amplifiers and continued this research while a Postdoctoral Research Associate with the University of Washington. He is currently an assistant professor in the electrical and computer engineering department at Rutgers, The State University of New Jersey.

His current research interests include low-power wireless circuits, energy scavenging, high-efficiency transmitter architectures and CMOS power amplifier design for software defined radio. Dr. Walling has authored over 30 articles in peer reviewed journals and refereed conferences. He received the Yang Award for outstanding graduate research from the University of Washington, Department of Electrical Engineering in 2008, an Intel Predoctoral Fellowship in 2007-2008, and the Analog Devices Outstanding Student Designer Award in 2006.

Nano-Relay Technology for Energy-Efficient Electronics

Abstract: As the era of traditional Complementary-Metal-Oxide-Semiconductor (CMOS) technology scaling is coming to an end, continual improvements in integrated-circuit (IC) performance and cost per function are becoming difficult to achieve without increasing power density. This necessitates the investigation of alternate device technologies that surmount the fundamental CMOS energy-efficiency limit and hence enable ultra-low-power ICs. To that end, a nano-electro-mechanical (NEM) relay technology is promising, because of its immeasurably low off-state leakage current and abrupt turn-on behavior, which provide for zero static power consumption and potentially very low dynamic power consumption.

In this talk, I will discuss recent research efforts in NEM relay technology, from both device- and circuit-level perspectives, which led to the successful demonstration of relay-based digital IC building blocks. In addition, I will discuss multi-input relay devices that can lead to smarter design and compact implementation of zero-leakage digital integrated circuits.

Biography: Jaeseok Jeon received the B.A.Sc. degree with first-class honours in electronics engineering from Simon Fraser University, Canada, in 2007 and the Ph.D. degree in electrical engineering from the University of California, Berkeley, in 2011. In 2011, he joined the Rutgers, the State University of New Jersey, as an assistant professor of Electrical and Computer Engineering.

In 2006, he was an electronics designer at Kodak Graphic Communications Canada Company, and he was awarded the 2006 NSERC-USRA award. He was a co-recipient of the 2011 ISSCC Jack Raper Award for Outstanding Technology Directions. His research interests include nano-electro-mechanical relay devices and technology for energy-efficient electronic systems and neural devices and circuits for efficient design of neuromorphic systems.

“Quantitative Data Convergence: Fusing radiology, pathology, omics data for predicting disease aggressiveness and patient outcome"

Abstract: Traditional biology generally looks at only a few aspects of an organism at a time and attempts to molecularly dissect diseases and study them part by part with the hope that the sum of knowledge of parts would help explain the operation of the whole. Rarely has this been a successful strategy to understand the causes and cures for complex diseases. The motivation for a systems based approach to disease understanding aims to understand how large numbers of interrelated health variables, gene expression profiling, its cellular architecture and microenvironment, as seen in its histological image features, its 3 dimensional tissue architecture and vascularization, as seen in dynamic contrast enhanced (DCE) MRI, and its metabolic features, as seen by Magnetic Resonance Spectroscopy (MRS) or Positron Emission Tomography (PET), result in emergence of definable phenotypes. At the Laboratory for Computational Imaging and Bioinformatics, we have been developing computerized knowledge alignment, representation, and fusion tools for integrating and correlating heterogeneous biological data spanning different spatial and temporal scales, modalities, and functionalities. The long term research objectives are to explore via efficient computational and pattern recognition methods, the existence and correspondence of biological patterns across heterogeneous data scales and modalities. An understanding of the interplays of different hierarchies of biological information from proteins, tissue, metabolites, and imaging will provide conceptual insights and practical innovations that will profoundly transform people’s lives.

ABSTRACT

Internet traffic grows exponentially in both the users and the traffic volume, which makes the backbone routers over-sized in the scale of interfaces and over-loaded in the processing power, while the energy consumption grows in a dramatically demand as well. In the traditional routers, the interface part and the packet processing part are one-to-one binding, which makes a low usage for the line-card when traffic is light, leading to high implementation cost, large energy consumption and rigid scalability when scaling to more network interfaces. To reduce the cost, cut down the power consumption and enhance the scalability, in this talk, I propose an architectural innovation for the future router design. I present a new architecture of router which separates router’s line-card into two parts: interface board and processing board. Traffic from all the interfaces is shared by all the processing boards in a router, so we can aggregate the traffic to several a few processing boards and shut down others to save energy when traffic is light. When the aggregated traffic is increasing, the router will wake up the sleeping processing card dynamically and adaptively in an on-demand manner. Given the aggregation of traffic from all ports of a router, there is a small probability that most of them reach up to a peak fluctuation simultaneously, so the entire utilization of processing parts of line cards should be low at most of the time. This gives us a great opportunity to reduce the power consumption of a high speed router.
I this talk, I will briefly describe the architectural innovation, and outline the challenging issues together with the preliminary simulation results.

BIOGRAPHY

Bin LIU is a full professor in Tsinghua University since 1999. He received his Ph D degree from Northwestern Polytechnical University, China in1993. His current research areas include high performance switches/routers, network processors, traffic measurement and management, Internet power saving as well as the future Internet. He co-authored the book of “High Performance Switches and Routers” and holds 21 patents in China and abroad. He has served as the TPC Co-Chair for the IWQoS2010, TPC Co-Chair for the Symposium on Next-Generation Networking and Internet Advances in ICC2011, the TPC Co-Chair for the Symposium of IEEE International Conference on Communications in ICC2008, Guest Editor for IEEE Journal on Selected Areas in Communications in 2006. He served as TPC members for many conferences/workshops such as IEEE INFOCOM. He has won a high volume of honors and rewards including the Distinguished Young Scholar of China and the National Top Young Scientist Award, the inaugural Applied Network Research Prize sponsored by IRTF and ISOC in 2011.

Abstract:

Consider a multiple input-multiple output (MIMO) interference channel whereby each transmitter and receiver are equipped with multiple antennas. An effective approach to practically achieving high system throughput is to deploy linear transceivers (or beamformers) that can optimally exploit the spatial characteristics of the channel. The recent work of Cadambe and Jafar suggests that optimal beamformers should maximize the total degrees of freedom and achieve interference alignment in the high signal to noise ratio (SNR) regime. In this talk, we examine several issues related to the design of a linear interference alignment scheme including its computational complexity, feasibility and practical algorithms to maximize the channel throughput.

Bio:

Zhi-Quan (Tom) Luo is a professor in the Department of Electrical and Computer Engineering at the University of Minnesota (Twin Cities) where he holds an endowed ADC Chair in digital technology. He received his B.Sc. degree in Applied Mathematics in 1984 from Peking University, China, and a Ph.D degree in Operations Research from MIT in 1989. From 1989 to 2003, Dr. Luo was with the Department of Electrical and Computer Engineering, McMaster University, Canada, where he later served as the department head and held a senior Canada Research Chair in Information Processing. His research interests lie in the union of optimization algorithms, data communication and signal processing.

Dr. Luo is a fellow of IEEE and SIAM. He is a recipient of the IEEE Signal Processing Society's Best Paper Award in 2004 and 2009, the EURASIP Best Paper Award and the ICC's Best Paper Award in 2011. He was awarded the Farkas Prize from the INFORMS Optimization Society in 2010. Dr. Luo currently chairs the IEEE Signal Processing Society's Technical Committee on Signal Processing for Communications and Networking (SPCOM). He has held editorial positions for several international journals including Journal of Optimization Theory and Applications, Mathematics of Computation, IEEE Transactions on Signal Processing, SIAM Journal on Optimization, Management Sciences and Mathematics of Operations Research.

The mm-wave frequency bands offer enormous potential for multi-Gb/s communications as well as emerging imaging and ranging applications. The realization of this potential will be underpinned by the development of high-performance, power-efficient transceivers in nanoscale CMOStechnologies. Two key challenges must be met towards achieving this goal. First, the mm-wave front-end circuits must be designed to operate over extremely wide bandwidths of several tens of GHz, both to exploit the large bandwidth availability, and also to provide sufficient margins to tolerate process, voltage and temperature variations that are increasingly problematic in nanoscale CMOS. Second, reducing power consumption in the front-end is imperative especially since phased-arrays are mandated in mm-wave transceivers. This talk presents circuit solutions to the aforementioned challenges. We introduce design approaches to the unilateralization of common-source and common-gate gain amplifiers, of both the narrowband and ultra-wideband varieties. We then present design techniques for mm-wave voltage-controlled oscillators that tune over several tens of GHz. These techniques are demonstrated through several CMOS prototypes operating in the 24 GHz and 60 GHz bands.

BIOSKETCH

Jeyanandh Paramesh received the B.Tech, degree from IIT, Madras, the M.S degree from Oregon State University and the Ph.D. degrees from the University of Washington, Seattle, all in Electrical Engineering. He is currently Assistant Professor of Electrical and Computer Engineering at Carnegie Mellon University. He has held product development positions with Analog Devices, where he designed high-performance data converters, and Motorola where he designed analog and RF integrated circuits for cellular transceivers. From 2002 to 2004, he was a graduate student researcher with the Communications Circuit Lab, Intel where he developed multi-antenna receivers, high-efficiency power amplifiers and high-speed data converters high data-rate wireless transceivers. His research interests include the design of RF and mixed-signal integrated circuits and systems for a wide variety of applications

Automobiles as Technology Platforms for a Personal Mobility Experience and a Better World

With more than a billion cars, trucks and buses on this planet and a relentless growth to the second billion, there is an immense and immediate opportunity for us all in the public, academic and private sectors to come together to make a lasting difference.

Automobiles pose a number of design challenges: they must jointly serve the desires of the consumer and the demands of society; they need to have an emotive appeal and yet must last at least 10 years or 150,000 miles, as a tightly regulated product; they are simultaneously complex cyber-physical systems and components of a much larger system-of-systems. Modern automobiles have transformed themselves into technology platforms to address these challenges and yet there is need to do much more so they can actively help reduce congestion, avoid or mitigate accidents, reduce fuel consumption, while offering all the conveniences of being digitally connected such as being able to call, hands-free, find parking and park, and being easily reprogrammable, to be rented or shared with little human intermediation.

The purpose of this talk is to share the excitement of designing automobiles as information and communication technology platforms and to stimulate a discussion of related cross-disciplinary collaboration opportunities.

Speaker Bio:

Dr. K. Venkatesh Prasad (class of 1990) is group and senior technical leader of Vehicle Design and Infotronics for Ford Research and Innovation. He is member of Ford’s 12-person global Technology Advisory Board, chaired by the CTO. Dr. Prasad is responsible for the research, architecture, standards, applications development and vehicle system integration of electrical, electronics and embedded software technologies.

Before joining Ford Motor Company in 1996, Prasad worked as a senior scientist at RICOH Innovations in Menlo Park, Calif., developing automatic "lip reading" as a novel human-machine interface. In addition, he was at Caltech and the NASA Jet Propulsion Laboratory in Pasadena, Calif., where he worked on the world's first telerobotic visual surface inspection system to help design the International Space Station.

Attracted by an open-ended challenge to discover ways to integrate "intelligence" into cars and trucks, Prasad joined Ford to work with a small group of engineers in the development of adaptive headlamp and lane-mark detection technologies.

The concept of stationarity is revisited from an operational perspective that explicitly takes into account the observation scale. A general, time-frequency-based, framework is described for testing such a relative stationarity via the introduction of stationarized surrogate data. Two variations are discussed, based on either dissimilarity measures between local and global spectra, or machine learning approaches. Different extensions, including wavelet-based tests for images and transient detection, are considered.

Bio
Patrick Flandrin is a CNRS Senior Researcher, working with the "Signals, Systems and Physics" Group in the Physics Department of Ecole Normale Supérieure de Lyon, France. His research interests are mostly in nonstationary signal processing (with emphasis on time-frequency methods and wavelets), scaling processes and complex systems. He authored numerous publications in those areas over the last 30 years, including the book "Time-Frequency/Time-Scale Analysis" (Academic Press, 1999). Dr Flandrin has been awarded the Philip Morris Scientific Prize in 1991, the SPIE Wavelet Pioneer Award in 2001 and the Prix Michel Monpetit from the French Academy of Sciences in 2001. Fellow of IEEE (2002) and EURASIP (2009), he has been elected Member of the French Academy of Sciences in 2010.

In recent years, in my group we have been working on various aspects of metamaterials and plasmonic nano-optics. We have introduced and been developing the concept of “metatronics”, i.e. metamaterial-inspired optical nanocircuitry, in which the three fields of “electronics”, “photonics” and “magnetics” can be brought together seamlessly under one umbrella – a paradigm which I call the “Unified Paradigm of Metatronics”.

In this novel optical circuitry, the nanostructures with specific values of permittivity and permeability may act as the lumped circuit elements such as nanocapacitors, nanoinductors and nanoresistors. Nonlinearity in metatronics can also provide us with novel optical nonlinear lumped elements. We have investigated the concept of metatronics through extensive analytical and numerical studies, computer simulations, and recently in a set of experiments at the IR wavelengths.

We have shown that nanorods made of low-stressed Si3N4 with properly designed cross sectional dimensions indeed function as lumped circuit elements at the IR wavelengths between 8 to 14 microns. We have been exploring how metamaterials can be exploited to control the flow of photons, analogous to what semiconductors do for electrons, providing the possibility of one-way flow of photons. We are now extending the concept of metatronics to other platforms such as graphene, which is a single atomically thin layer of carbon atoms, with unusual conductivity functions. We study the graphene as a new paradigm for metatronic circuitry and also as a “flatland” platform for IR metamaterials and transformation optics, leading to the concepts of one -atom-thick metamaterials, and one-atom-thick circuit elements and optical devices. I will give an overview of our most recent results in these fields.

This ECE Colloquium will be held in the CoRE Building Auditorium on Busch Campus.

Adaptive networks consist of spatially distributed agents that are linked together through a connection topology. The topology may vary with time and the agents may also move. The agents cooperate with each other through local interactions and by means of in-network processing. The diffusion of information across the network results in various forms of self-organizing behavior and collective intelligence. A key property of adaptive networks is that all agents behave in an isotropic manner and are assumed to have similar abilities. This kind of behavior is common in many socio-economic and life and biological networks where no single agent is in command. Adaptive networks are well-suited to perform decentralized information processing and decentralized inference tasks. They are also well-suited to model self-organizing behavior such as animal flocking and swarming. This talk describes research results on distributed processing over adaptive networks and illustrates the techniques by studying self-organization in biological networks such as bird formations, fish schooling, bee swarming, and bacteria motility.
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A H. Sayed is Professor of Electrical Engineering and Director of the UCLA Adaptive Systems Laboratory. His research areas span adaptation and learning mechanisms, adaptive and cognitive networks, bio-inspired information processing, distributed and statistical signal processing. He has published 5 books and over 350 articles. His work received several awards including the 1996 IEEE Fink Prize, the 2003 Kuwait Prize, the 2005 Terman Award, and two Best Paper Awards from the IEEE Signal Processing Society (2002, 2005). He is a Fellow of IEEE and served as Editor-in-Chief of the IEEE Transactions on Signal Processing (2003-2005) and as 2005 Distinguished Lecturer of the IEEE SP Society. He is currently serving as Vice-President of Publications of the same Society.

Abstract:

Recent advances in signal processing, sensing, and computing have facilitated the development of new technologies with the potential for enhancing musical expression, interaction, and education. This presentation will highlight research by the Music & Entertainment Technology Laboratory (MET-lab) at Drexel University exploring music, emotion, and creative expression under the common vision of making music more interactive and accessible for both musicians and non-musicians. These projects encompass the recognition of emotion, such as a system for dynamic musical mood prediction and a collaborative web game for the collection of emotional annotations, as well as interfaces for expressive performance, including a novel electromagnetic approach to shaping the sound of the acoustic piano and a user-friendly controller for remixing music in terms of emotion. Recent work has also used humanoid robots to explore aspects of musical instrument performance and understanding. These and other MET-lab efforts are closely coupled with educational initiatives, many of which have been deployed in K-12 outreach programs in the Philadelphia region, to promote learning in Science, Technology, Engineering, and Mathematics (STEM).
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Biography:

Youngmoo Kim is an Assistant Professor of Electrical and Computer Engineering at Drexel University. His research group, the Music & Entertainment Technology Laboratory (MET-lab) focuses on the machine understanding of audio, particularly for music information retrieval. Other areas of active research at MET-lab include analysis-synthesis of sound, human-machine interfaces and robotics for expressive interaction, and K-12 outreach for engineering, science, and mathematics education. Youngmoo received his Ph.D. from the MIT Media Lab in 2003 and also holds Masters degrees in Electrical Engineering and Music (Vocal Performance Practice) from Stanford University. He served as a member of the MPEG standards committee, contributing to the MPEG-4 and MPEG-7 audio standards, and he co-chaired the 2008 International Conference on Music Information Retrieval (hosted at Drexel). His research is supported by the National Science Foundation and the NAMM Foundation, including an NSF CAREER award in 2007.

Refreshments will be served.

This is part of the ECE Colloquium Series. Please contact Professor Yanyong Zhang (yyzhang [at] winlab [dot] rutgers [dot] edu) for further information.