Colloquia

ECE Colloquium


The Electrical & Computer Engineering Colloquium Series brings to campus accomplished scholars and industry leaders to share the excitement of research and creative engineering across the broad spectrum of electrical and computer technology. All students are encouraged to attend and explore the power and possibilities of these emerging technologies. Admission is free and open to all. Lectures are followed by a brief question and answer session.

Vish Ishaya - Nebula, Chief Technical Officer

Friday, May 2, 2014 - 3:00pm - 4:00pm

CoRE Lecture Hall

Title: OpenStack and the Unique Challenges of Running a Cloud in a Next Generation Data Center

Abstract

Discussion on OpenStack and the unique challenges of running a cloud in a next generation data center. Cloud development methodologies mean different approaches to problems. These approaches bring with them a new set of concerns. Why businesses and universities are deploying and adopting private clouds. OpenStack is a cloud toolkit, so the early-adopters are building and leveraging private clouds. These tend to be leading universities, DOD, service providers and large enterprises. In addition, high growth internet businesses that need to scalability and agility. These companies started solving business problems using virtualization and public clouds but are now looking for cloud flexibility and functionality in their own data centers,
under their control and behind the firewall.

Biography

Vish Ishaya, Nebula CTO - Vish Ishaya was previously Nebula's Director of Open Source and prior to that was a Principal Engineer with Rackspace Cloud Builders. He was also a Senior Systems Engineer with Anso Labs and NASA Nebula Technical Lead during the creation of Nova, one of the founding OpenStack projects. He is a highly prolific developer who was one of the founding engineers and a top contributor to OpenStack. During the November 2010 OpenStack conference, he won an OpenStack award for his development and community efforts, and was also elected to the first OpenStack Technical Committee, where he has served consistently since.

Vish was elected to four consecutive terms as the OpenStack Compute Project Technical Lead and is currently on the board of OpenStack Foundation. In addition to his programming and systems skills, Vish has spent over a decade teaching, most recently classes in object oriented analysis and design.

Dr. Seongshik Oh, Rutgers, Department of Physics & Astronomy

Wednesday, April 30, 2014 - 10:00am - 11:00am

CoRE Building Lecture Hall

Title: Atomic-layer-by-layer molecular beam epitaxy for topological insulators and artificial functional oxides

Abstract

Molecular beam epitaxy (MBE), which was invented in late 1960s in Bell lab and advanced over the past decades, allows growth of various thin film structures with atomic precision. In particular, it led to a number of major breakthroughs in semiconductor systems such as fractional quantum Hall effect, high electron mobility transistor (HEMT) and quantum cascade lasers. In our lab, we are applying this MBE technology beyond the conventional semiconductors to investigate novel materials such as topological insulators and artificial functional oxides that are either difficult or impossible to grow using other methods. Topological insulators (TI) are a new class of materials that were discovered several years ago and are being heavily investigated, yet mostly in the physics community. One of the most intriguing properties of TIs is that they are supposed to have highly mobile metallic surface states while inside of the material is insulating. However, real TIs suffer from serious material problems that make the utilization of these surface states nearly impossible. In this talk, I will overview the MBE technology and how it can be used to study topological insulators and functional oxides. Then, I will discuss how we utilize this technique to overcome the material problems of TIs and implement various novel TI platforms.

Bio

Seongshik Oh received his Ph.D. in Physics from University of Illinois, Urbana-Champaign in 2003 and was a postdoctoral researcher at National Institute of Standards and Technology, Boulder between 2004 and 2007. In 2007 he joined the faculty of Department of Physics and Astronomy at Rutgers University, where he is currently an Associate Professor. His research interests are in synthesis and electronic properties of two dimensional quantum materials and devices. He received the NSF CAREER award and published over 50 journal articles and book chapters. More details can be found in his group website: mbe.rutgers.edu

Dr. Gil Zussman, Columbia University

Wednesday, April 9, 2014 - 10:00am - 11:00am

CoRE Building Lecture Hall




Energy Harvesting Active Networked Tags (EnHANTs) — Measurements, Algorithms, and Prototyping

Abstract

We discuss a new type of wireless devices in the domain between RFIDs and sensor networks – Energy Harvesting Active Networked Tags (EnHANTs - http://enhants.ee.columbia.edu). Future EnHANTs will be small, flexible, and self-powered devices that can be attached to objects that are traditionally not networked (e.g., books, toys, clothing), thereby providing the infrastructure for various Internet-of-Things tracking applications. We describe the paradigm shifts associated with the underlying enabling technologies. Then, we present the results of an indoor light energy measurement campaign and of a kinetic energy study that have been conducted in order to characterize the energy availability for EnHANTs. We discuss low complexity energy-harvesting-adaptive algorithms which aim to allocate resources uniformly in respect to time and to determine energy and data rate allocations for a node and for a link. Finally, we present the design considerations for the EnHANT prototypes which harvest indoor light energy using custom organic solar cells, communicate and form multihop networks using ultralow-power Ultra-Wideband Impulse Radio (UWB-IR) transceivers, and adapt their communications and networking patterns to the energy harvesting and battery states. We also describe a small scale EnHANTs testbed that uniquely allows evaluating different algorithms with trace-based light energy inputs and discuss experimental results.

Based on joint works with A. Bernstein, M. Gorlatova, R. Margolies, A. Wallwater, and the groups of P. Kinget, J. Kymissis, D. Rubenstein, and L. Carloni (Columbia).

Bio

Gil Zussman received the Ph.D. degree in electrical engineering from the Technion in 2004 and was a postdoctoral associate at MIT between 2004 and 2007. In 2008 he joined the faculty of the Department of Electrical Engineering at
Columbia University where he is currently an Associate Professor. His research interests are in the areas of wireless, mobile, and resilient networks. He is a co-recipient of 5 paper awards, including the ACM SIGMETRICS'06 Best Paper Award and the 2011 IEEE Communications Society Award for Outstanding Paper on New Communication Topics. He received the Fulbright Fellowship, two Marie Curie Fellowships, the DTRA Young Investigator Award, and the NSF CAREER Award. He was also the PI of a team that won first place in the 2009 Vodafone Americas Foundation Wireless Innovation Project competition.

J. Rockey Luo, Associate Professor, ECE, Colorado State University

Wednesday, April 2, 2014 - 10:00am - 11:00am

CoRE Building Lecture Hall

Coding Theory and Access Control for Distributed Wireless Networking

Abstract:

Classical network architecture assumes that communication optimization should be done at the physical layer. Data link layer only determines whether and when users should transmit packets. In a multiuser system, under the assumption that data link layer should efficiently schedule multiuser communication activities, classical channel coding has been focusing on coordinated communication scenarios where users jointly optimize their channel codes and communication parameters. As wireless networks are getting increasing complex and dynamic, scheduling the communication of a large number of users in a long time duration can be very difficult. Consequently, a significant proportion of messages in wireless networks are transmitted using distributed communication protocols. In these scenarios, users are not fully coordinated to optimize communication at the physical layer, and therefore data link layer should often get involved in communication adaptation. Unfortunately, not only that distributed communication is not well supported by classical channel coding theory at the physical layer, classical link layer model is also not able to support advanced communication adaptation due to the simple binary transmit/idle options of the users.

In this talk, we present a Shannon-style channel coding theory developed for distributed communication systems where users do not jointly design channel codes. We show that fundamental performance limitation of a distributed multiple access system can be characterized using an achievable region defined in a sense quite different from the classical ones. The new channel coding theory, which can indeed be viewed as an extension of the classical Shannon theory, enabled an enhanced physical-link layer interface where link layer users can now be equipped with more than two options to transmit their packets. At the data link layer, we formulate the distributed channel access problem as a non- coorperative game where each user optimizes an individual utility function. By assuming a general form of the utility functions, conditions under which the distributed channel access game possesses a unique Nash equilibrium is obtained. Simulation results show that when link layer users are provided with multiple transmission options, their behavior in distributed communication adaptation, as an outcome of the non-cooperative channel access game, tend to agree with the well known information theoretic understandings.

Bio:

J. Rockey Luo received the Ph.D. degree in Electrical and Computer Engineering from University of Connecticut in 2002. From 2002 to 2006, he was a Research Associate with the Institute for Systems Research (ISR), University of Maryland, College Park. Since 2006, he has been with the Electrical and Computer Engineering Department of Colorado State University where he is currently an Associate Professor. His areas of research interests are communication networks, information theory, and signal processing.

Dr. George Celler, Rutgers University, IAMDN

Wednesday, March 26, 2014 - 10:00am - 11:00am

CoRE Building Lecture Hall


Semiconductor Technology Roadmap, its purpose and some examples

Abstract:   Global semiconductor business exceeds $350B in annual revenues, and semiconductor processing equipment adds additional $50B/year. Even though the technology companies fiercely compete with each other, there is also a lot of interdependence, as nobody can do it alone. Each semiconductor manufacturer depends on a vast infrastructure of hardware and software suppliers. In this highly dynamic environment, rapid progress as marked by Moore's law that predicts (and effectively requires) doubling of integrated circuit performance every two years would not be possible without a large degree of coordination between all the technology participants. For this purpose a roadmapping organization was formed in 1991, and it has evolved into a large team effort that develops and maintains the International Technology Roadmap for Semiconductors (ITRS).

I will describe the motivation for the ITRS and related roadmapping activities and how the roadmap is developed. Then I will provide some examples of what the ITRS is predicting for the future electronic devices

Biography:   Dr. George K Celler received his Ph.D. in physics from Purdue University. He is a Research Professor at the Materials Science and Engineering Dept. and the Institute for Advanced Materials, Devices, and Nanotechnology (IAMDN) at Rutgers University. Previously he was Chief Scientist at Soitec USA, where he was responsible for technical interactions and collaborations with the US industry and academia in the field of substrate engineering. Before joining Soitec in 2001, he spent 25 years at Bell Laboratories, where he was a Distinguished Member of Technical Staff and Technical Manager. In addition to his long-term interest in silicon-on-insulator structures and their applications, he also investigated laser annealing and rapid thermal processing of semiconductors, diffusion phenomena in Si and silicon dioxide, and electro-optical properties of GaAs. He led a large DARPA supported x-ray lithography program at Bell Labs and was a Deputy Manager of X-Ray Lithography Consortium. He published over 200 articles, edited nine books, and was issued 22 US patents. He is a fellow of the American Physical Society and of The Electrochemical Society, and a member of IEEE, OSA, and MRS. From 2002 to 2012 he led a SOI subcommittee of the International Technology Roadmap for Semiconductors (ITRS) and a SOI Standards subcommittee of SEMI. He is a member of the Board of MIT Microphotonics Consortium and a member of External Advisory Board of the NSF-funded MRSEC at Georgia Tech. on epitaxial graphene. He is an Associate Editor of the ECS Journal of Solid State Science and Technology, and the ECS Solid State Letters.

Dr. Jose Moura, Carnegie Mellon University

Wednesday, February 26, 2014 - 10:00am - 11:00am

CoRE Building Lecture Hall

Data & Models: Correlation and Causation

A few years ago Chris Anderson, Editor in Chief of Wired Magazine, proposed the “End of Theory;” no need for causation (modeling), from data (big) with Google smarts (or the likes) get all the correlations needed . We live in a time of great challenge and opportunity. Data is big, but, more importantly, comes in all sorts of ways and from many different sources – social, physical, biological, molecular, to name a few. However, if we do capture the relations among data through (arbitrary) graphs (and this in itself is a big if), we can recapture the “big data” challenge in the very familiar setting of everyone’s beloved DSP. This talk will overview our progress so far extending to signals and data defined on graphs traditional signal processing concepts including shifting, frequency, filtering, convolution, spectral representation, filters frequency response, linear transforms like the discrete Fourier transform. With a proper setting, models still make sense and help interpret the data. We illustrate with examples drawn from social networks and the World Wide Web.

Work with Dr. Aliaksei Sandryhaila and graduate student Jonathan Mei.

José M. F. Moura is a visiting Professor at CUSP, NYU (2013-14). He is the Philip and Marsha Dowd University Professor at Carnegie Mellon University, with interests in statistical signal processing (SP) and distributed SP on graphs. He was an IEEE Board Director (2013-2014), he was President of the IEEE Signal Processing Society (SPS), and was Editor in Chief for the Transactions on SP. Moura received several awards including the IEEE Signal Processing Society Technical Achievement Award and the IEEE Signal Processing Society Society Award for outstanding technical contributions and leadership in SP. He is a Fellow of the IEEE, a Fellow of AAAS, a corresponding member of the Academy of Sciences of Portugal, and a member of the US National Academy of Engineering.

Dr. Aylin Yener, Pennsylvania State University

Thursday, February 20, 2014 - 4:00pm - 5:00pm

Core Building Lecture Hall

Energy Harvesting Wireless Communication Networks

Abstract: Wireless communication networks composed of devices that can harvest energy from nature will lead to the green future of wireless, as energy harvesting offers the possibility of perpetual network operation without adverse effects on the environment. By developing effective and robust communication techniques to be used under energy harvesting conditions, some of the communication devices and networks can even be taken off the grid. Energy harvesting brings new considerations to system level design of wireless communication networks, leading to new insights. These include randomness and intermittency of available energy, as well as additional system issues to be concerned about such as energy storage capacity and processing complexity. The goal of this talk is to furnish the audience with fundamental design principles of energy harvesting wireless communication networks established in our recent work. The focus will be on identifying optimum transmission scheduling policies in various settings, the ensuing algorithmic solutions leading to design insights, and time permitting, some recent results on information theoretic limits.

Bio

Aylin Yener received the B.Sc. degree in electrical and electronics engineering, and the B.Sc. degree in physics, from Bogazici University, Istanbul, Turkey; and the M.S. and Ph.D. degrees in electrical and computer engineering from Wireless Information Network Laboratory (WINLAB), Rutgers University, New Brunswick, NJ. Commencing fall 2000, for three semesters, she was a P.C. Rossin endowed assistant professor at the Electrical Engineering and Computer Science Department, Lehigh University, PA. In 2002, she joined the faculty of The Pennsylvania State University, University Park, PA, where she was an assistant Professor, then associate Professor, and is currently professor of Electrical Engineering since 2010. During the academic year 2008-2009, she was a visiting associate professor with the Department of Electrical Engineering, Stanford University, CA. Her research interests are in wireless communications and networking, information theory, communication theory and network science, with recent emphasis on energy harvesting green communications and information security. She received the NSF CAREER award in 2003 and the Penn State Engineering Alumni Society Outstanding Research Award in 2010; and was a co-recipient of DARPA young investigator team award for the ITMANET program in 2006, and the best paper award in Communication Theory Symposium at the IEEE International Conference on Communications in 2010.

Dr. Yener has served as a technical program (co-)chair for various conferences including for the IEEE Communications Society (2008-2014). She was an associate editor for the IEEE Transactions on Communications (2009-2012), an associate editor and an editorial advisory board member for the IEEE Transactions on Wireless Communications (2001-2012). She served as the student committee chair for the IEEE Information Theory Society 2007-2011, and was the co-founder of the Annual School of Information Theory in North America in 2008. Dr. Yener is a member of the board of governors of the IEEE Information Theory Society and its treasurer since 2012.

Dr. Laura Fabris, Rutgers University, Dept. of Materials Science & Engineering

Wednesday, February 12, 2014 - 10:00am - 11:00am

CoRE Building Lecture Hall

Gold Nanoparticles for Imaging and Sensing

Abstract

Gold nanoparticles have seen a widespread growth in application because of their many useful features, such as ease of synthesis, the stability, the non-cytotoxicity, but mainly because of their intriguing optical properties. The optical properties of gold nanoparticles are characterized by the coherent oscillation of their conduction electrons at the interface between the metal and the surrounding dielectric medium, and can give rise to intense absorption bands whose position mainly depends on the shape of the nanoparticle. One of the techniquesin which gold nanoparticles have found vast application is surface enhanced Raman spectroscopty (SERS), a non-linear near field technique that takes advantage of the intense electromagnetic field enhancement that takes place in close proximity to the surface of the nanoparticle. This enhancement is particularly intense at specific locations called "hot-spots". In this talk I will present our experiments aimed at increasing the SERS enhancement by carefully tailoring the hot spots.

First of all, I will describe our results in the preparation of multifunctional gold NP dimers capable of specific cell targeting, optimized uptake, and highly resolved cel imaging that outperforms fluorescence. The systems presented here will be based on spherical NP dimers targeting U87 glioblastoma cells. Dithiolated linkers have been used to lock the NPs in a dimer conformation and also act as SERS reporters. In our experiments, thiolated PEG was used to stabilize the NP systems, while cyclic RGD peptides were employed to target avb3 integrins overexpressed on the surface of cancerous cells. Combined analysis carried out via fluorescence and Raman microscopy demonstrated the efficient SERS=based imaging of U87 cells that outperformed fluorescence.

In a second set of results, I will describe the use of gold nanostars. Gold nanostars are nanoparticles with a spherical core and very sharp spikes, who sharpness can be modulated by tuning the synthetic parameters. In this work, we have synthesized gold nanostars and deposited them on a gold substrate via a bifunctional tether, hence locking them on the surface. The sharp spikes of the nanostars act as excellent hot spots enabling the use of these substrates for SERS-based chemical sensing. We have demonstrated that this sensor is able to selectively identify both chemisorbed and physisorbed analytes down to the femtomolar regime with high selectivity and multiplexing ability.

Bio

Dr. Fabris earned her B.S./M.S. in Physical Chemistry at the University of Padova, Italy. After a one-year experience in industry she returned to graduate school to pursue her Doctorate Degree in Chemical Sciences, always at the University of Padova. Her dissertation work focused on the synthesis and characterization of peptide protected gold nanoclusters. She then took a postdoctoral position in the Department of Chemistry and Biochemistry at the University of California at Santa Barbara, where she remained until June 2009. Her work entailsed the development of surface enhanced Raman scattering (SERS)-based biosensors. In July 2009 she joined the Department of Materials Science and Engineering, where is is currently an Assistant Professor. Dr. Fabris is also a Graduate Faculty member of the Departments of Chemistry and Chemical Biology and Biomedical Engineering at Rutgers. Her research is targeting the study of plasmonic nanoparticles and their application as tags for SERS-based cell imaging and for the efficiency enhancement of plasmonic organic solar cells.

Dr. Bijan Pesaran, New York University

Wednesday, December 4, 2013 - 10:00am - 12:00pm

CoRE Lecture Hall

Abstract:

The study of the brain is enjoying an era of growth with dramatic advances in our knowledge of the link between brain and behavior. Research is leading to a better scientific understanding of how the brain controls behavior and is opening up translational opportunities to engineer devices that replace lost brain function. Our understanding of brain mechanisms is largely based on the spiking activity of individual neurons. In this talk, I will argue that an exclusive focus on spiking activity hampers both basic neuroscience and neural engineering. I will develop a complementary approach involving local field potentials (LFPs), electrical potentials generated by populations of neurons. I propose that LFPs show promise in two specific areas. Local field potentials can improve our scientific understanding of how different brain areas communicate with each other during behavior and can accelerate the development of robust high-performance neural interfaces that replace lost brain function.

Bio:

Bijan Pesaran completed his undergraduate training in Physics at the University of Cambridge, UK. He went on to earn his PhD in Physics at the California Institute of Technology in 2002. He then completed postdoctoral research in Biology until 2005. He has been on the faculty at New York University since 2006 where he is currently Associate Professor of Neural Science in the Center for Neural Science. Among his other honors he has received a Sloan Research Fellowship, a McKnight Scholar Award and an NSF CAREER Award.

Dr. K. J. Ray Liu,
Christine Kim Eminent Professor of Information Technology,
Department of Electrical and Computer Engineering,
University of Maryland, College Park

Wednesday, November 20, 2013 - 10:00am - 12:00pm

CoRE Building Lecture Hall

Title:   A Time-Reversal Paradigm for Green Internet of Things

Abstract

In recent years, with the explosive growth of wireless communication, the energy consumption of wireless networks and devices is experiencing a dramatic increase. Because of ubiquity of wireless applications, such increasing energy consumption not only results in a high operational cost and an urgent demand for battery/energy capacity to wireless communications operators, but also causes a more severe electromagnetic pollution to the global environment. Therefore, an emerging concept of "Green Communications" has received considerable attention in hope of finding novel solutions to improve energy efficiency, relieve/reduce radio pollution to unintended users, and maintain/improve performance metrics.

To qualify as a green wireless technology, one must meet two basic requirements: one is low energy consumption (environmental concerns) and the other is low radio pollution to others (health concerns) besides the intended transmitter and receiver. In the first part of the talk, we argue and show that the time-reversal (TR) signal transmission is an ideal paradigm for green wireless communications because of its inherent nature to fully harvest energy from the surrounding environment by exploiting the multi-path propagation to re-collect all the signal energy that would have otherwise been lost in most existing communication paradigms. Our theoretical analysis and simulations show that a potential of over an order of magnitude of power reduction and interference alleviation can be achieved. We also demonstrate a very high multi-path diversity gain exhibiting in a TR system. In essence, TR transmission treats each multi-path as a virtual antenna and makes full use of all the multi-paths. Experimental results obtained from measurements in real RF multi-path environment are shown to demonstrate the great potential of TR-based transmission as an energy-efficient green wireless communication paradigm. In the second part, we will demonstrate why the TR paradigm is an ideal technology for the future green Internet of Things.

Bio:

Dr. K. J. Ray Liu was named a Distinguished Scholar-Teacher of University of Maryland in 2007, where he is Christine Kim Eminent Professor of Information Technology. He leads the Maryland Signals and Information Group conducting research encompassing broad areas of signal processing and communications with recent focus on cooperative communications, cognitive networking, social learning and networks, and information forensics and security. Dr. Liu has received numerous honors and awards including IEEE Signal Processing Society 2009 Technical Achievement Award. A Fellow of the IEEE and AAAS, he is recognized by Thomson Reuters as an ISI Highly Cited Researcher. Dr. Liu is President of IEEE Signal Processing Society. He was the Editor-in-Chief of IEEE Signal Processing Magazine and the founding Editor-in-Chief of EURASIP Journal on Advances in Signal Processing. Dr. Liu also received various research and teaching recognitions from the University of Maryland, including Poole and Kent Senior Faculty Teaching Award, Outstanding Faculty Research Award, and Outstanding Faculty Service Award, all from A. James Clark School of Engineering; and Invention of the Year Award from Office of Technology Commercialization.

Dr. Chao Tian, AT&T Research

Wednesday, November 13, 2013 - 10:00am - 12:00pm

CoRE Building Lecture Hall

Title: New Results on Regenerating Codes for Distributed Data Storage

Abstract: In large data centers and peer-to-peer data storage systems, traditional erasure codes such as Reed-Solomon codes incur a high repair cost when a node fails, and thus new repair-efficient codes are urgently needed. Despite extensive recent efforts, it remains an open problem whether the cut-set outer bound can indeed be achieved. In the first part of the talk I provide an answer (in the negative) to this problem by completely characterizing the rate-region of the code under a specific set of parameters. The main difficulty in establishing this result is the converse part, and the traditional manual proof approach used by information theorists for the past 60 years appears quite infeasible here. A computer-aided proof (CAP) approach is thus developed, by taking into account the symmetry in the problem, and moreover utilizing the linear programming duality, to yield an explicit algebraic proof. In the second part of the talk, I briefly discuss a new code construction based on layered error correction and combinatorial block designs, which can achieve new operating points that are not possible using existing constructions.

Bio: Dr. Tian received the B.E. degree in Electronic Engineering from Tsinghua University, Beijing, China, in 2000 and the M.S. and Ph. D. degrees in Electrical and Computer Engineering from Cornell University, Ithaca, NY in 2003 and 2005, respectively. He was a postdoctoral researcher at Swiss Federal Institute of Technology at Lausanne (EPFL) from 2005 to 2007, and then joined AT&T Labs-Research, Florham Park, New Jersey. Dr. Tian received the Liu-Memorial Award at Cornell University in 2004, and AT&T Key Contributor Award in 2010 and 2011. He is an associate editor of the IEEE Signal Processing Letters, and an adjunct associate professor at Columbia University.

Dave Wilson, Director of Academic Programs, National Instruments

Thursday, November 7, 2013 - 11:00am - 12:00pm

CoRE Bldg Board Room, Room 701

Title: Engineering the Future using Systems Design

How do students prepare to engineer the future? How will expectations for higher level functionality change the knowledge requirements of engineers? This presentation will explore the spectrum of components and skills that engineering students need to possess when they graduate. We will tour the fundamental components of electronics, mechanics and programming. And then look at the ways to efficiently combine them into systems that will serve to meet the most challenging demands on science and engineering. With NI's vast array of research and industry applications, we will take a close look at some advanced applications that are redefining capabilities and resetting expectations on what can be accomplished. And, most importantly, we~Rll comment on paths students are taking to be prepared to participate immediately upon graduating and enter the world ready to "Do Engineering".

Biography:

As the Director of Training and Academic Programs for National Instruments, Dave Wilson works with the both NI headquarters and more than 45 NI branches around the globe. He ensures the most effective product proficiency development strategies and tactics are implemented worldwide.

Before joining NI, Dave worked for the Xerox Corporation and Keithley Instruments as a research engineer and software developer. Upon joining NI in 1991 as a Michigan-area district sales manager, he began driving the adoption of NI measurement and automation solutions throughout the automotive industry. In this role, he presented more than 50 technical seminars, wrote hundreds of applications with customers, and received multiple industry recognition awards.

In 1995, Wilson became the director of data acquisition marketing where he led several successful launches for products that have become key parts of the NI product line including motion control, Vision, DAQ boards, and PXI. He also developed product and corporate messages and led initiatives to work with R&D to incorporate customer-recommended features into new products. In 2000, Wilson became the international sales director for NI Japan where he led the branch to record growth.

Wilson has delivered more than 60 keynotes about the application of next-generation technologies in 30 countries in Asia, Europe and the Americas. He has met with the ministers of education in both Russia and Kosovo and many Deans of engineering to discuss ways to adopt new generation technologies for science and engineering in university curricula. He has also authored numerous articles and interviewed with multiple domestic and international publications including EE Times Asia, Bits & Chips, Evaluation Engineering, Desktop Engineering, and Sensors.

Additionally, Wilson has chaired the most successful customer recognition event held by NI, the Graphical System Design Achievement Awards. For ten years, this event has recognized NI customers around the world for accomplishments in engineering and science.

Wilson holds a bachelor of science degree in applied physics from the State University of New York.

Dr. Steven McLaughlin, Georgia Tech

Wednesday, November 6, 2013 - 10:00am - 12:00pm

CoRE Building Lecture Hall

Dr. Peter Ramadge, Princeton University

Wednesday, October 30, 2013 - 10:00am - 12:00pm

CoRE Building Lecture Hall

Abstract:

The sparse representation of signals with respect to an over-complete dictionary has been of recent interest in a broad range of applications. One of the most used methods for obtaining sparse codes, the Lasso problem, becomes computationally costly for large dictionaries and this hinders the use of this approach for large-scale decision tasks. Recently, dictionary screening has been used to address this computational issue.

In this spirit, this talk shows how sequential Lasso screening can also facilitate faster completion of sparse representation decision tasks, such as classification, without a major impact on statistical accuracy. The sequential screening process allows us to employ an early decision mechanism that can accelerate classification, possibly at the cost of small decrease in accuracy. The talk will discuss the theoretical background that underlies these methods and demonstrate results on several classification tasks. In particular, for clip-level music genre classification, using scattering features and a new voting scheme, we show that the proposed method yields improved clip classification accuracy and considerable computational speedup.

Bio:

Dr. Peter Ramadge received the B.Sc. and B.E. degrees and the M.E. degree from the University of Newcastle, Australia, and the Ph.D. degree from the Department of Electrical Engineering at the University of Toronto, Canada. He joined the faculty of Princeton University in September 1984, where he is currently Gordon Y.S. Wu Professor of Engineering, and Professor of Electrical Engineering.

Dr. Ramadge has been a visiting Professor at the Massachusetts Institute of Technology and a Visiting Research Scientist at IBM's Tokyo Research Laboratory. He is a Fellow of the IEEE and a member of SIAM. He has received several honors and awards including: a paper selected for inclusion in IEEE book "Control Theory: Twenty Five Seminal Papers (1932-1981)", an Outstanding Paper Award from the Control Systems Society of the IEEE and is listed in ISIHighlyCited.com. His current research is in the domain of statistical signal processing and machine learning, and fMRI data analysis.

Andrew Grimshaw, University of Virginia

Wednesday, October 23, 2013 - 1:00pm - 2:00pm

CoRE Building Lecture Hall

Abstract

Lowering the barriers to collaboration and increasing access to high-end resources will accelerate the pace and productivity of science and engineering. Toward this end, the eXtreme Science and Engineering Discovery Environment (XSEDE) is a single virtual system that allows scientists to seamlessly and interactively share computing resources, data, and expertise. The XSEDE project will allow researches to link and access resources at both domestic and foreign supercomputing centers as well as resources belonging to university campuses and research labs around the world. The complexity of distributed systems creates obstacles for scientists who wish to share their resources with collaborators. Obstacles include: complex, unreliable, and unfamiliar tools and environments; multiple administrative domains each with their own passwords and file systems; the need to keep track of which resources are on which machines; the need to manually copy files and applications from place to place; the need to monitor and interact with multiple execution services, each with their own idiosyncratic behavior; and the need to manage authorization, identities and groups. The best way to manage complexity and make sharing data and resources possible on a large scale to provide users with a familiar, easy-to-use tool that manages aspects of the collaboration on the user’s behalf. The first principle of XSEDE’s approach to designing a collaborative interface is familiarity: give the user interaction paradigms and too ls that are similar to those she already uses. XSEDE deploys what it calls the Global Federated File System (GFFS) in order to leverage the user’s familiarity with the directory-based paradigm.

The GFFS is a global shared namespace designed so that the user can easily organize and interact with files, execution engines, identity services, running jobs, and much more. Many types of resources, such as compute clusters, directory trees in local file systems, and storage resources, can be linked into the GFFS
directory structure by resource owners at centers, on campuses, and in individual research labs. GFFS resources can be accessed (subject to access control) in a variety of ways: from the command line (useful for scripting); via a GUI; or by being mapped directly into the local file system. When mapped into the local file system, remote resources can be accessed by existing applications as if they were local resources. In this talk I will present the GFFS, its functionality, its motivation, as well as typical use cases. I will demonstrate many of its capabilities, including: how to secure shared data with collaborators; how to share storage with collaborators; how to access data at the centers from campus and vice versa; how to create shared compute queues with collaborators who can then schedule jobs on collaboration “owned” resources; how to create jobs and how to interact with them once started. I will present the GFFS’s various access mechanisms, i.e., the GUI and local file system mapping; if facilities permit, I will include this latter mechanism in the live demonstration.

Bio

Dr. Andrew Grimshaw received his Ph.D. from the University of Illinois at Urbana-Champaign in 1988. He joined the University of Virginia as an Assistant Professor of Computer Science, becoming Associate Professor in 1994 and Professor in 1999. He is the chief designer and architect of Mentat, Legion, Genesis II, and the co-architect for XSEDE. In 1999 he co-founded Avaki Corporation, and served as its Chairman and Chief Technical Officer until 2003. In 2003 he won the Frost and Sullivan Technology Innovation Award. In 2008 he became the founding director of the University of Virginia Alliance for Computational Science and Engineering (UVACSE). The mission of UVACSE is to change the culture of computation at the University of Virginia and to accelerate computationally oriented research.

Andrew is a leading member of the Open Grid Forum (OGF), serving both as a member of the OGF's Board of Directors and as Architecture Area Director. Andrew is the author or co-author of over 50 publications and book chapters. His current projects are Genesis II and XSEDE. Genesis II, is an opensource, standards-based, Grid system that focuses on making Grids easy-to-use and accessible to non computer-scientists. XSEDE (eXtreme Science and Engineering Discovery Environment) is the NSF follow-on to the TeraGrid project.

Dr. Judy Qiu, School of Informatics and Computing, Indiana University at Bloomington

Friday, October 18, 2013 - 10:00am - 12:00pm

CoRE Lecture Hall

Abstract

Many scientific applications are data intensive. It is estimated that organizations with high- end computing infrastructures and data centers are doubling the amount of data that they are archiving every year. Twister extends MapReduce, enabling HPC-Cloud Interoperability. We show how to apply Twister to support large-scale iterative computations that are common in many important data mining and machine learning applications. Furthermore, one needs additional communication patterns from those familiar in MapReduce. This leads us to the new Map-Collective programming model which we develop here based on requirements of a range of applications by extending our existing data analysis framework Twister. The resultant Map-Collective model, which captures the full range of traditional MapReduce and MPI features, is built on a new communication abstraction. It will be integrated with Hadoop and evaluated with Twister, HDinsight and Twister4Azure. Our work includes a detailed performance evaluation on IaaS or HPC environments such as Azure, FutureGrid and IU’s Big Red II supercomputer, and provides useful insights to both frameworks and applications.

Bio

Dr. Judy Qiu is an Assistant Professor of Computer Science in the School of Informatics and Computing at Indiana University and an assistant director of the school’s Digital Science Center. Her research interests are parallel and distributed systems, cloud computing, and high-performance computing. Qiu leads the SALSA project, involving professional staff and Ph.D. students from the School of Informatics and Computing. SALSA focuses on data-intensive computing at the intersection of cloud and multicore technologies with an emphasis on scientific data analysis applications by using MapReduce and traditional parallel computing approaches. Her research has been funded by NSF, NIH, Microsoft, Google and Indiana University. She is a recipient of NSF CAREER Award in 2012

Dr. William Pence, WebMD

Wednesday, October 16, 2013 - 10:00am - 12:00pm

CoRE Building Lecture Hall

Title:   WebMD Mobile: Overview of WebMD Mobile Services and Opportunities for Users and Advertisers

Abstract:

WebMD is the world's largest mobile health information provider, with more than 24M monthly unique users on their consumer mobile web site alone. WebMD has also introduced a compelling line of mobile apps for consumer and health care providers, and more recently has started to introduce features that allow physicians and consumers to connect, for users to create more personalized experiences, and for new forms of data to be captured and leveraged.

In this talk I will provide an overview of WebMD's scale and lines of business, describe new ways that WebMD is leveraging data to create more personalized user experiences and enable novel advertising and sponsorship messages, and new apps that enable a future world of connected wearable devices and digital connections between consumers and their health care providers and medical data.

Bio:

Executive Vice President, Chief Operating Officer and Chief Technology Officer William Pence has served as Executive Vice President and Chief Technology Officer of WebMD since November 2007 and has also served Chief Operating Officer of WebMD since May 2012. Before joining WebMD, Mr. Pence had served as Chief Technology Officer and Senior Vice President at Napster since 2003. From 2000 to 2003, Mr. Pence was the Chief Technology Officer for Universal Music Group's online initiatives and for the pressplay joint venture with Sony. That joint venture later served as the basis for the relaunched Napster service. Previously, Mr. Pence spent more than a decade at IBM, where he held various technology management positions in research as well as in the software division, focused on guiding research and development and commercializing technology for IBM product divisions. Mr. Pence received a Bachelor of Science in Physics from the University of Virginia, and a Ph.D. in Electrical Engineering from Cornell University.

Dr. Frank Bentley, Yahoo! Research

Wednesday, October 9, 2013 - 10:00am - 12:00pm

CoRE Building Lecture Hall

Title:

Health Mashups: Encouraging behavior change through identifying long-term patterns between wellbeing data and context

Abstract:

People now have access to many sources of data about their health and wellbeing. Yet, most people cannot wade thr-ough all of this data to answer basic questions about their long-term wellbeing: Do I gain weight when I have busy days? Do I walk more when I work in the city office? Do I sleep better on nights after I work out?

We built the Health Mashups system to identify connections that are significant over time between weight, sleep, step count, calendar data, location, weather, pain, food intake, and mood. These significant observations are displayed in a mobile application using natural language, e.g. "You are happier on days when you sleep more." We performed a pilot study, made improvements to the system, and then conducted a 90-day trial with 60 diverse participants, learning that interactions between wellbeing and context are highly individual and that our system supported an increased self-understanding that lead to focused behavior changes.

Bio:

Frank Bentley is a Principal Research Scientist in Mobile Sensing and User Behavior Research at Yahoo! Labs in California. Frank's work investigates the ways in which mobile devices can help strengthen strong-tie social relationships. He takes projects from early conceptual studies through to prototyping, field evaluation, and product as a routine process. Frank recently joined Yahoo! after 11 years at Motorola Labs in Chicago. He also teaches a Mobile HCI class at MIT and recently completed a book, Building Mobile Experiences, with MIT Press.

Dr. Selin Aviyente, Michigan State University

Wednesday, September 25, 2013 - 11:00am - 12:00pm

CoRE Building Lecture Hall

Title: A Signal Processing Framework for Studying Dynamic Functional Brain Networks

Abstract: Increasingly sophisticated neuroimaging methods have opened up important areas of basic research in psychiatry, psychology, and neurology. These neuroimaging modalities pose new challenges and opportunities for the signal processing community to analyze highly complex, multi-dimensional and dynamic data. One particular challenge is the identification of dynamic functional networks underlying observed neural activity. Current imaging modalities index local neural activity very well, but there is an increasing need for methods that provide measures of the interaction between regional activations. In this talk, I will focus on signal processing methods to quantify this interaction between different brain regions based on the electroencephalogram (EEG) measurement of the brain activity. In the first part of the talk, I will present phase synchronization as a plausible mechanism for modeling the reciprocal interactions between local networks of the brain. In order to quantify the time varying nature of interactions through phase synchronization, a new time-frequency phase synchrony (TFPS) measure based on Rihaczek distribution will be introduced. Graph theoretic methods to characterize the topology of functional connectivity networks constructed by this new synchrony measure will be discussed. In the second part of the talk, I will present subspace analysis based methods for extracting information from time-varying functional connectivity networks. Finally, application of the proposed methods to EEG data containing the error-related negativity (ERN), a brain potential response that indexes endogenous action monitoring, will be presented.

Bio:

Selin Aviyente received her B.S. degree with high honors in electrical and electronics engineering from Bogazici University, Istanbul in 1997. She received her M.S. and Ph.D. degrees, both in Electrical Engineering: Systems, from the University of Michigan, Ann Arbor, in 1999 and 2002, respectively. Currently, she is an associate professor in the Department of Electrical and Computer Engineering at Michigan State University. Her research focuses on statistical signal processing, in particular non-stationary signal analysis, with applications to biological signals. Her most recent work focuses on the study of the functional networks in the brain. She is the recipient of 2005 Withrow Teaching Excellence Award and 2008 NSF CAREER Award.


Prof. Janne Lindqvist, Department of Electrical & Computer Engineering, Rutgers University

Wednesday, September 11, 2013 - 10:00am - 12:00pm

CAIT Auditorium 100 Brett Road

Title:Nudging People with Computer Systems

Abstract:
Computer systems today affect directly or indirectly billions of people. For example, using mobile phones directly integrates computer systems into people’s daily lives. In this talk, I will present my research program on redesigning computer systems for detecting and nudging behavior change. We will discuss how to redesign mobile phone platforms to make privacy-sensitive sensor access (e.g. localization) transparent to users, and how this affects their behavior. We will also discuss how similar approaches can be used for other important societal purposes including password security, mitigating distracted driving and bringing people together in local communities.

Bio:
Janne Lindqvist is an assistant professor of Electrical and Computer Engineering and a member of WINLAB at Rutgers University. Janne leads the Rutgers Human-Computer Interaction group. From 2011-2013, Janne was an assistant research professor of ECE at Rutgers.

Prior to Rutgers, Janne was a post-doc with the Human-Computer Interaction Institute at Carnegie Mellon University’s School of Computer Science. Janne received his M.Sc. degree in 2005, and D.Sc. degree in 2009, both in Computer Science and Engineering from Helsinki University of Technology, Finland. He works at the intersection of human-computer interaction, mobile computing and security engineering. Before joining academia, Janne co-founded a wireless networks company, Radionet, which was represented in 24 countries before being sold to Florida-based Airspan Networks in 2005. His work has been featured several times in MIT Technology Review and recently also in New York Times, phys.org, Tech Republic, and other online venues. During his first year at Rutgers, Janne was awarded three NSF grants totaling nearly $1.3 million and a MobiCom best paper award.

Dr. Stephen Hughes, Queens University, Canada

Tuesday, April 30, 2013 - 10:00am - 12:00pm

CoRE Building Lecture Hall

Dr. Alicia Abella, AT&T Labs Research

Wednesday, April 24, 2013 - 1:00pm - 2:00pm

CoRE Building Lecture Hall

Title: Empowering Devices

Abstract

When I think back, at a device and its accompanying service that truly gave people an unexpected new ability I can¹t help but think back to the invention of the telephone itself. When I think about what people had to do prior to that to talk to their loved ones or friends, they basically had to get on a boat, a horse, or walk for miles. Not only was this long, it was dangerous. The telephone made it possible for people to talk to other people from the comfort of their home. Today we can not only hear each other but see each other too. Whether your across the street or around the globe. In this talk I will review a research program at AT&T Labs - Research called Empowering Devices. The vision of this research work is to create novel devices and companion services that will exploit the wireless and wired network to stimulate demand, while exciting people with unexpected new abilities.

Biography

Dr. Abella is Executive Director of the Innovative Devices and Services Research Department at AT&T Labs, where she manages a group of multi-disciplinary technical staff specializing in human-computer interaction, mobile services, SIP/VoIP technology, ubiquitous computing, and emerging devices.

In May 2013, Dr. Abella will receive Columbia University’s Medal of Excellence, an award given each year to an alumnus or alumna, under 45 years of age, whose record in scholarship, public service, or professional life is outstanding. This is the first time since 1929 -- when the award was first given -- that Columbia has awarded the medal to an engineer. In 2011, she was selected by President Obama to be on his Presidential Advisory Commission for Educational Excellence for Hispanics. Also in 2011, she was inducted into the prestigious WITI(Women in Technology International) Hall of Fame. In 2010, she was honored as one of the Top Five Women of the Year by Hispanic Business Magazine. She is also a member of the elite group of AT&T Science and Technology Medal award winners and recipient of the Hispanic Engineers National Achievement Award for Outstanding Technical Achievement.

Besides her technical contributions, Dr. Abella has been a strong advocate infostering the development of minorities and women in science and engineering. As Executive Vice President for the Young Science Achievers program,a program she has been involved with for 9 years, she has worked tirelessly to bring an interest and excitement in science and engineering to high school aged women and minority students through a program of mentoring and scientific achievement.

Following completion of her Ph.D. in Computer Science from Columbia University in 1995, Dr. Abella joined AT&T Bell Laboratories in Murray Hill, NJ where she began her work in the problem of natural language understanding and dialog management. In addition to her doctoral work, Dr. Abella received a MS from Columbia and BS from NYU, both in Computer Science. She lives in Morristown, New Jersey, with her husband Alex and their son Mark.


Dr. Mohammad Ali Maddah-Ali, Bell Labs, Alcatel-Lucent

Wednesday, April 17, 2013 - 10:00am - 12:00pm

CoRE Building Lecture Hall

Title: Fundamental Limits of Caching

Abstract

Caching is a technique to reduce peak traffic rates by prefetching popular content in memories at the end users. Conventionally, cache memories are exploited by delivering requested contents in part locally rather than through the network. In this talk, we present a novel caching approach that can achieve a significantly larger reduction in peak rate compared to previously known caching schemes. In particular, the improvement can be on the order of the number of end users in the network. In the proposed approach, the cache placement is carefully designed in order to create multicasting opportunities even among users with different demands. Using an information theoretic argument, we show that the proposed scheme is within a constant factor from "capacity" for all values of the problem parameters.

This is a joint work with Urs Niesen.

Biography

Mohammad Ali Maddah-Ali received the PhD from the University of Waterloo, Waterloo, ON, Canada. From March 2007 to December 2007, he was working at the Wireless Technology Laboratories, Nortel Networks, Ottawa, ON, Canada, in a joint program between University of Waterloo and Nortel Networks. From January 2008 to August 2010, he was a Postdoctoral Fellow at the Wireless Foundations Center, Department of Electrical Engineering and Computer Sciences, the University of California at Berkeley. Since September 2010, he has been with Bell Laboratories, Alcatel-Lucent, Holmdel, NJ, as a communication networks research scientist. His research interests include wireless communications and network information theory.


Dr. Ananya Sen Gupta, University of Iowa

Wednesday, April 10, 2013 - 10:00am - 11:00am

CoRE Building Lecture Hall

Title: "Studying the environment as a complex system: breaking the barrier of traditional assumptions"

Abstract

Traditional signal processing approaches are often built on well-known assumptions such as linearity, time-invariance, and incoherence among the signals involved. In reality, many of these assumptions are violated in physical environments and therefore, conventional techniques fail to solve signal processing issues effectively in real-world systems. For example, a classic challenge to quantifying the environmental impact of a major oil spill such as the 2010 Macondo well spill in the Gulf of Mexico lies in distinguishing its fingerprint against closely correlated natural seeps and other reservoirs in the area. Multi-user detection in the presence of high correlation and amplifier saturation, tracking the time- varying delay spread of shallow water acoustic channels, sonar detection against severe clutter, among many other applications also face similar challenges.

My talk will focus on some of these problems encountered in challenging physical environments, such as the ocean, as they relate my research in adaptive signal processing, sparse optimization and signal separation techniques. While the techniques I will discuss have been developed with target applications in mind, the scope of signal processing innovations go beyond specific applications to the broader paradigm of other well-known problems with similar issues. In particular, I will present my vision on how breaking the barrier of traditional assumptions and constraints can enable the scientific study of the environment as a diverse, complex and dynamic system, with the end goal of enhancing better balance between anthropogenic activities and environmental health and sustenance.

Biography

Dr. Ananya Sen Gupta got her MS (Aug. 2001) and PhD (Dec. 2006) in Electrical Engineering from the University of Illinois at Urbana-Champaign. Her broad area of expertise is signal processing, particularly interference mitigation, channel estimation and sparse optimization techniques. Throughout her research career Dr. Sen Gupta has been interested in seeking novel solutions for signal processing challenges commonly encountered in real environments. Her Master's research was in dynamic MRI imaging under the supervision of Dr. Zh-Pei Liang, and her doctoral research was in non-linear multi-user interference suppression under the supervision of Dr. Andrew Singer. Aug 2008-2012 she has been a postdoctoral researcher at the Woods Hole Oceanographic Institution under the supervision of Dr. James Preisig, working in shallow water acoustic channel tracking using adaptive sparse optimization techniques. As her continuing position at WHOI, she has been actively collaborating with Dr. Christopher Reddy to develop novel informational methods that provide collective forensic interpretation of petroleum samples found in the ocean using comprehensive two-dimensional gas chromatography. More recently, she has joined the University of Iowa, Department of Electrical and Computer Engineering, as tenure-track faculty. Her active research interests involve signal processing challenges commonly encountered in complex environments, with particular focus on fingerprinting and sparse optimization across a variety of applications.


Dr. Jie Liu, Microsoft Research

Monday, April 8, 2013 - 10:00am - 12:00pm

CoRE Building Lecture Hall

Title: "A Fresh Look at Mobile Location Sensing"

Abstract

Location-based services have become ubiquitous thank to sensors like GPS and WiFi in our smart phones and other mobile devices. However, continuous location sensing such as logging, tracking, and geo-fencing, consume too much energy and shorten device battery life. In this talk, we take a fresh look at location sensing, in both outdoor and indoor settings. For outdoor location, we dive into the principles of GPS receivers and show that by offloading GPS processing to the cloud, we can reduce the device side energy consumption by three orders of magnitude. For indoor location, we discover that commercial FM signals are good sources of location signatures that work better than WiFi signatures by themself, and works even better if combined with WiFi signatures. These low energy alternatives enable always-there location services without users paying battery life penalty.

Presentation Slides of Dr. Liu's talk
The Presentation slides (pdf) of Dr. Jie Liu's talk entitled "A Fresh Look at Mobile Location Sensing" are located   here.

Biography

Dr. Jie Liu is a Principal Researcher at Microsoft Research, Redmond, WA, and the manager of its Sensing and Energy Research Group. His research interests root in understanding and managing the physical properties of computing. Examples include timing, location, energy, and the awareness of and impact on the physical world. He has published broadly in areas like sensor networks, embedded systems, ubiquitous computing, and energy efficient cloud computing. Dr. Liu is an Associate Editor of ACM Trans. on Sensor Networks, has been an Associate Editor of the IEEE Trans. on Mobile Computing, and has chaired a number of top tier conferences. He is an ACM Distinguished Scientist. Dr. Liu received his Ph.D. degree from Electrical Engineering and Computer Sciences, UC Berkeley in 2001. From 2001 to 2004, he was a research scientist at Palo Alto Research Center (formerly Xerox PARC).


Prof. Ilan Lobel
Stern School of Business
New York University

Wednesday, April 3, 2013 - 10:00am - 11:00am

CoRE Building Lecture Hall

Title: "Inter-temporal Price Discrimination: Structure and Computation of Optimal Policies"

Abstract

We consider the question of how should a firm optimally set a sequence of prices in order to maximize its long-term average revenue given a continuous flow of strategic customers. In particular, customers arrive over time, are strategic in timing their purchases and are heterogeneous along two dimensions: their valuation for the firm's product and their willingness to wait before purchasing or leaving. The customers' patience and valuation may be correlated in an arbitrary fashion. For this general formulation, we prove that the firm may restrict attention to short cyclic pricing policies, which have length twice the maximum willingness to wait of the customer population. We further establish results on the subpotimality of monotone pricing policies in general, and illustrate the structure of optimal policies. These are, in a typical scenario, characterized by nested sales, where the firm offers partial discounts throughout each cycle, offers a significant discount halfway through the cycle, with the largest discount offered at the end of the cycle. From a computational perspective, we exploit the structure of the underlying problem to develop a novel dynamic programming formulation for the problem that computes an optimal pricing policy in polynomial time (in the maximum willingness-to-wait). We further establish a form of equivalence between the problem of pricing for a stream of heterogeneous strategic customers and pricing for a pool of heterogeneous customers who may stockpile units of the product. Joint work with Omar Besbes (Columbia).

The paper is available here:
http://pages.stern.nyu.edu/~ilobel/IntertemporalPriceDiscrimination.pdf

Biography

Dr. Ilan Lobel is an Assistant Professor of Information, Operations and Management Sciences at New York University's Stern School of Business. Prior to joining NYU Stern in 2010, he was a post-doctoral researcher at the Microsoft Research New England Lab. He received his Ph.D. in Operations Research from the Massachusetts Institute of Technology in 2009 and his B.Sc. in Electrical Engineering from the Pontificia Universidade Catolica of Rio de Janeiro in 2004. Professor Lobel's research focuses on the operations of Internet-based businesses, including issues such as pricing, learning and contract design in online, dynamic and networked markets. His work focuses on application domains such as online advertisement, cloud computing and social networks.


Dr. Chang-Hwan Choi
Steven's Institute of Technology

Wednesday, March 27, 2013 - 1:00pm - 2:00pm

CoRE Building Lecture Hall


Dr. William Arnold
Chief Scientist and Vice President of Technology Development Center
ASML

Monday, March 11, 2013 - 11:00am - 12:00pm

CoRE Building Lecture Hall

Abstract

Lithography is used to pattern semiconductor devices such as memories and processors. Water immersion lithography using the ArF excimer laser source at 193nm is the key manufacturing tool today. EUV lithography is developed to continue the shrink of integrated circuit features below 20nm half pitch.

Laser produced plasma sources operating at 13.5nm are used with all-reflective optics to expose resists. This presentation will describe the status of EUVL and the remaining challenges to bring it into high volume manufacturing by 2015.

Biography

Bill Arnold is for 15 years the chief scientist of ASML, the world's leading supplier of lithography equipment for semiconductor manufacturing. He is also Sr. Vice President of the ASML Technology Development Center. Before that he was 18 years with Advanced Micro Devices, a leading manufacturer of microprocessors. He had many jobs over time at AMD, the last being Director of Advanced Process Development and Sr. Fellow. In 2013, Mr. Arnold is the President of SPIE, the International Society for Optics and Photonics.


Dr. Demetrios Christodoulides
CREOL-College of Optics and Photonics
University of Central Florida

Thursday, March 7, 2013 - 10:00am - 11:00am

CoRE Building Room 701 Boardroom

Title:    Exploring similarities between classical and quantum systems

Abstract

Analogies between different disciplines provide a powerful tool in understanding nature. As such, quantum-classical optical similarities offer new opportunities in manipulating classical optical fields or quantum states. In recent years, many of the ramifications of these concepts have come to fruition on several fronts in the general area of optics. What made this possible are some new advances in structure fabrication and beam synthesis techniques. In this talk, we will provide an overview of our activities in this field. As an example, we will consider accelerating optical wavepackets in the form Airy beams as a means to bend light for applications in plasmonics, extreme nonlinear optics, and biology. Studying quantum inspired phenomena in artificial optical structures that would have been otherwise impossible to directly observe in their own habitat, like Anderson localization, parity-time (PT) symmetry, Bloch oscillations, Klein tunneling, etc. will be discussed. Finally, the possibility of quantum state engineering in periodic and random optical lattices will be reviewed in this talk.

Biography

Demetri Christodoulides is a Provost’s Distinguished Research Professor at CREOL-the College of Optics and Photonics of the University of Central Florida. He received his Ph.D. degree from Johns Hopkins University in 1986 and he subsequently joined Bellcore as a post-doctoral fellow at Murray Hill. Between 1988 and 2002 he was with the faculty of the Department of Electrical Engineering at Lehigh University. His research interests include linear and nonlinear optical beam interactions, synthetic optical materials, optical solitons, and quantum electronics. He has authored and co-authored more than 250 papers. He is a Fellow of the Optical Society of America and the American Physical Society. In 2011 he received the R.W. Wood Prize of OSA.


Dr. Michela Taufer
University of Delaware

Wednesday, March 6, 2013 - 10:00am - 11:00am

CoRE Building Lecture Hall

Title: Transforming computing algorithms and paradigms in HPC to enable more science out of our day-to-day simulations

Abstract

My research group at the University of Delaware is engaged in interdisciplinary research with scientists and engineers in fields such as chemistry, chemical engineering, pharmaceutical sciences, seismology, and mathematics. The group's mission is to increase scientific discovery by transforming the way scientific applications deploy high performance computing (HPC) including distributed and multi-core systems. Several research vignettes will be presented that show how we have been successful in addressing challenges in science such as classifying protein-ligand binding geometries of billions of ligands in molecular docking in linear time, performing accurate simulations of fully atomistic macromolecular systems at meso-length and time scales, and improving numerical reproducibility and stability of MD simulations on multi-core platforms.

Biography

Michela Taufer joined the University of Delaware in 2007 as an assistant professor. She was promoted to associate professor with tenure in 2012. In January 2013 she was named the David L. and Beverly J.C. Mills Chair of Computer and Information Sciences. She earned her master's degrees in Computer Engineering from the University of Padova (Italy) and her doctoral degree in Computer Science from the Swiss Federal Institute of Technology (Switzerland). Taufer completed her postdoctoral studies as a La Jolla Interfaces in Sciences Fellow at the Center for Theoretical Biological Physics (CTBP), at the University of California, San Diego. Taufer's research focuses on efficient computational algorithms and adaptive scheduling policies for scientific computing on HPC platforms including multi-core, cloud, and volunteer computing.


Dr. Nicolas Madamopoulos
The City College of New York

Friday, March 1, 2013 - 10:00am - 11:00am

CoRE Building Lecture Hall

Title:    Selective "Light" Redirection For Information Processing and Energy Conservation

Abstract

Processing “light” provides solutions in medical systems, metrology, telecommunications, industrial and environmental sensing, energy and sustainable environment. In this lecture, two examples of selective “light” redirection for signal processing and energy conservation will be presented. In the first example, the development of a tunable-bandwidth optical filter for applications in telecommunications, sensors and RF/microwave signal processing is described. The approach is based on an all-fiber-optic dynamically tunable Michelson-Gires-Tournois Interferometer (MGTI) that incorporates broadband fiber-optic based loop mirrors. These fiber loop mirrors provide a wide range of tunable relativity (e.g., 0-100%) and enable a variety of transfer functions, such as notch, rectangular pass-band and comb filters using the same basic platform. The second example highlights a more “classical” optical system that enables windows to become from the weakest link the in building envelope and energy “losers”, to energy managers and potentially energy “suppliers”. The concept is based on an active façade implementation for selective redirection of incoming solar radiation with a dual goal to harvest (a) the visible part of the spectrum for efficient daylighting and (b) the thermal energy of the incoming solar radiation for heating/cooling assistance. Both of these goal lead to reduced energy consumption, reduced carbon footprint and increased occupant comfort.

Biography

Dr. N. Madamopoulos is an Associate Professor in the Department of Electrical Engineering at the City College of New York (CCNY), of the City University of New York (CUNY). He is leading the research and educational efforts at the Optics and Photonics Systems Laboratory. He is also the Assistant Director of the Building Performance Lab, CUNY Institute for Urban Systems. Before joining CCNY, he held various Senior Research positions in the industry (Corning, Inc, Lucent – Bell Labs, Calient Networks) and research institutions (National Hellenic Research Foundation; Foundation For Research and Technology-Hellas, Department of Electrical and Computer Engineering -UCSB, The School of Optics/CREOL). His work has been widely recognized and honored with several international awards by the OSA, IEEE, and SPIE.

Professor Madamopoulos received a BS in Physics from the University of Patras, Greece, in 1993, a M.Sc. and a Ph.D. degree in Optical Science and Engineering from The College of Optics & Photonics/CREOL (Center for Research and Education in Optics and Lasers), University of Central Florida, in 1996 and 1998, respectively.


Dr. Irina Rish
IBM, Thomas J. Watson Research Center

Wednesday, February 27, 2013 - 10:00am - 11:00am

CoRE Building Lecture Hall

Sparsity and Interpretability in Predictive Multivariate Analysis of fMRI Data

Abstract

One of the central topics in statistical analysis of fMRI data is discovering brain areas relevant to a given stimuli or mental state. Herein, we focus on predictive accuracy as a better relevance measure than the traditional voxel activations based on univariate voxel correlations with stimulus, since the latter approach ignores potentially important multivariate voxel interactions.

Since an exhaustive search over all subsets of voxels is intractable, sparse (l1-regularized) regression is a popular alternative for learning predictive models simultaneously with selection of predictive subsets of voxels, since l1 constraint on the regression model parameters tends to find solutions with relatively small number of nonzeros. However, multiple well-predicting sparse solutions may exist when the variables are highly correlated, as it is the case in fMRI data. Thus, while the brain areas included into a highly predictive sparse solution are clearly relevant to the task, it is not clear how unique such solutions are, i.e. how much information about the task is still contained in the rest of the brain.

This leads to the following questions: should one expect a sharp boundary between task-relevant and task-irrelevant brain areas, or rather a widespread distribution of task-relevant information across the whole brain? How does the task-related information distribution depend on the properties of the task? Herein, empirical exploration of such boundary is performed using the Elastic Net regression when predicting several stimuli and/or behavior variables from fMRI, including pain perception, visual stimulus rating, and several behavioral measures recorded during videogame playing (PBAIC 2007 data). Interestingly, for most of the tasks, no clear separation between relevant and irrelevant areas is observed, with the only exception of a relatively simple auditory task.

Thus, we hypothesize that complex tasks tend to involve most of the brain rather than just specific areas, which points in the direction of ``holographic'' information representation for such tasks, while simpler tasks yield more clear separation between relevant and irrelevant areas. These observations suggest a novel methodological approach that goes beyond traditional voxel activation maps and involves a more comprehensive evaluation of information spread in the brain.

Biography

Irina Rish , is a Research Staff Member (RSM) at IBM T.J. Watson Research Center. She received her MS in Applied Mathematics from Moscow Gubkin Institute, Russia, and PhD in Computer Science from the University of California, Irvine. Irina Rish research interests are in the areas of probabilistic inference, machine learning, and information theory. Particularly, she has done work on approximate inference in graphical models, information-theoretic experiment design and active learning, with applications are in the area of autonomic computing - automated management of complex distributed systems, which includes various diagnosis, prediction and online decision-making problems. Irina Rish’s current research is in the area of machine-learning applications to computational biology and neuroscience, with a particular focus on statistical analysis of brain imaging data such as fMRI.


Dr.. Naveen Verma
Princeton University

Wednesday, February 13, 2013 - 1:00pm - 2:00pm

CoRE Building Lecture Hall

Abstract

Think about some of the physical systems with which we would like electronics to engage in valuable interactions: physiological systems, high‐value industrial equipment, critical infrastructure…. These systems are complex, both in terms of the number of signals they present, and in terms of how those signals represent information. In this talk I will describe some of the hardware platforms we are pursuing to handle these complexities. By ‘interacting with a physically‐complex world’, I am referring to an ability to make sense of embedded signals when in fact we may have no tractable analytical models for the underlying processes. Instead, we look at how sensor data can be used as a knowledge base, exploiting the tremendous data‐acquisition capabilities of next‐generation sensor networks towards the construction of high‐quality data‐driven models. Machine learning gives us powerful frameworks for data‐driven analysis; the question is how to create very‐low‐power hardware to enable such frameworks in energy‐constrained sensor devices. I will describe our work on low‐power medical sensors for disease monitoring and harm detection. Interacting with a physically‐complex world also implies the ability to acquire embedded signals on a very large scale, in fact much larger than traditional integrated‐circuit technologies can possibly handle. Large‐area electronics is a technology that can enable the creation of large arrays of diverse transducers for sensing. To build complete systems, however, substantial embedded computation, instrumentation, and power management is also required. We focus on scalable methods for combining large‐area electronics with CMOS ICs to exploit the complementary strengths of the two technologies. I will describe our work towards smart infrastructure, using flexible sensing sheets to build systems for high‐resolution structural‐health monitoring of bridges.

 
Biography

Dr. Verma received the B.A.Sc. degree in Electrical and Computer Engineering from the University of British Columbia, Vancouver, Canada in 2003 and the M.S. and Ph.D. degrees in Electrical Engineering from Massachusetts Institute of Technology in 2005 and 2009 respectively. Since July 2009 he has been an Assistant Professor of Electrical Engineering at Princeton University. His research focuses on advanced sensing systems, including low‐voltage digital logic and SRAMs, low‐noise analog instrumentation and data‐conversion, large‐area sensing arrays based on flexible electronics, and low‐ energy algorithms for embedded inference especially for medical applications.


Dr. Jason Stauth
Dartmouth College

Wednesday, February 6, 2013 - 10:00am - 12:00pm

CoRE Building Lecture Hall

Abstract

The viability of photovoltaic energy has increased tremendously in the last decade as new manufacturing capacity (especially in China) has driven PV module costs to levels never thought possible. However, there remain challenges in achieving true grid-cost-parity for PV compared to other sources such as coal and natural gas. These challenges include balance of system components and system integration costs, both of which are now major focuses of the DOE. This talk will discuss PV systems from a general perspective, targeting audience members who have less exposure to the PV area. The basic configurations of PV systems will be presented from the cell, module, string, array, and power plant level. We will then drill down into the different architectures for the power management system including central inverter, micro-inverter, and other emerging architectures. New classes of multi- level DC-DC converter ‘partial-power processing’ circuits will be presented as next-generation solutions.

Biography

Dr. Stauth received his MS and PhD degrees at University of California, Berkeley in 2006 and 2008 respectively. At U.C. Berkeley Dr. Stauth was affiliated with the Berkeley Wireless Research Center (BWRC) and the Power Electronics Research Group, studying under Prof. Seth Sanders. His research focused on high frequency power electronics and RF integrated circuits. In 2008 he co-founded QVSense, Inc. and operated as CTO until QVSense was acquired by Solar Semiconductor. He remained as Director of Hardware Engineering at Solar Semiconductor until 2011. Since 2011 he has been Assistant Professor at Dartmouth College.


Dr. Trac D. Tran,
Johns Hopkins University

Wednesday, December 5, 2012 - 10:00am - 12:00pm

CoRE Building Lecture Hall

Abstract:

Most natural signals can be approximately represented by a few coefficients with respect to certain basis that carry the most relevant information. Processing of the signals in the sparsifying domain is much faster and simpler than in the original domain. This makes signal sparsity an extremely powerful tool in many classical signal processing applications. On the other hand, in many signal processing applications involving highly non-stationary signals such as images and videos, local adaptivity also plays a very important role in capturing the rich spatial/temporal/spectral correlation structure. In this talk, I will introduce the development of sparsity-constrained optimization algorithms based on content- or data-adaptive dictionary design for discriminative applications (detection, classification, and recognition). The proposed framework is applicable in a variety of practical discriminative applications, provided the assumption that signals lie in a union of low-dimensional subspaces holds.

I will particularly concentrate on target detection and classification for hyperspectral imagery. However, if time permits, I will also discuss other applications such as robust face recognition and other research directions in the area of sparse signal processing at Johns Hopkins.

Biography:

Trac D. Tran S'94-M'98-SM'08 received the B.S. and M.S. degrees from the Massachusetts Institute of Technology, Cambridge, in 1993 and 1994, respectively, and the Ph.D. degree from the University of Wisconsin, Madison, in 1998, all in Electrical Engineering.

In July of 1998, Dr. Tran joined the Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD, where he was recently promoted to the rank of Professor. His research interests are in the field of digital signal processing, particularly in sparse representation, sparse recovery, sampling, multi-rate systems, filter banks, transforms, wavelets, and their applications in signal analysis, compression, processing, and communications. His pioneering research on integer-coefficient transforms and pre-/post-filtering operators has been adopted as critical components of Microsoft Windows Media Video 9 and JPEG XR - the latest international still-image compression standard ISO/IEC 29199-2.

Dr. Tran was the co-director (with Prof. J. L. Prince) of the 33rd Annual Conference on Information Sciences and Systems (CISS'99), Baltimore, MD, in March 1999. In the summer of 2002, he was an ASEE/ONR Summer Faculty Research Fellow at the Naval Air Warfare Center & Weapons Division (NAWCWD) at China Lake, California. He is currently a regular consultant for the U.S. Army Research Laboratory in Adelphi, Maryland. Dr. Tran has served as Associate Editor of the IEEE Transactions on Signal Processing as well as IEEE Transactions on Image Processing. He was a former member of the IEEE Technical Committee on Signal Processing Theory and Methods (SPTM TC) and is a current member of the IEEE Image Video and Multidimensional Signal Processing (IVMSP) Technical Committee. He is currently serving his second term as an Associate Editor for IEEE Transactions on Signal Processing.

Prof. Tran received the NSF CAREER award in 2001, the William H. Huggins Excellence in Teaching Award from The Johns Hopkins University in 2007, and the Capers and Marion McDonald Award for Excellence in Mentoring and Advising in 2009.


Dr. Vijay Narayanan, Pennsylvania State University

Wednesday, November 14, 2012 - 10:00am - 12:00pm

CoRE Building Lecture Hall

Abstract:

While machine vision research has continued to improve multi-fold over the past few decades, it still significantly falls short of the abilities and efficiencies of the primate visual cortex system. The primate brain is especially superior as pertains to comprehending and interacting with complex natural environments. In energy-efficiencies, the brain is estimated to be around four orders better than current machine vision solutions. While there is much consensus on the superiority of biological vision systems over machine systems on most vision tasks, the approaches leading to the better efficiencies and flexibility akin to the visual cortex are still widely debated. In this talk, I will highlight recent efforts at architecting customized digital hardware systems using neuromorphic algorithms as one successful approach to achieving better energy efficiencies. I will also provide insight to how emerging devices are influencing novel implementations of such hardware systems.

Biography:

Vijaykrishnan Narayanan is a Professor of Computer Science and Engineering and Electrical Engineering at The Pennsylvania State University. His research and teaching interests include embedded systems, computer architecture, system design using emerging device technologies and power-aware computing. He has deep interests in cross-disciplinary advances and has led and participated in such projects. He is the deputy editor-in-chief of IEEE TCAD and served as the editor-in-chief for ACM Journal of Emerging Technologies in Computing Systems. He has won several awards including the 2012 ASPDAC Ten-year retrospective Most influential paper, 2012 Penn State Alumni Society Premier Research Award and 2010 Outstanding Alumnus Award from SVCE, India. He is a fellow of IEEE. He has worked with several outstanding students who are currently in industry and academia throughout the world.

Dr. Minjoo Lee, Yale University

Wednesday, November 7, 2012 - 10:00am - 12:00pm

CoRE Building Lecture Hall

Abstract:

In this talk, I will present progress on three projects in my group that are unified by their need for strained or lattice-mismatched growth. The first topic is molecular beam epitaxy (MBE) of metamorphic InGaP and GaAsP for solar cells. Our interest in metamorphic InGaP stems from the fact that its bandgap can be tuned to values as high as ~2.2 eV. Such high bandgap materials will be necessary for multi-junction solar cells to reach 60% efficiency, but mismatched epitaxy is required since the compositions of interest do not possess the same lattice constant as common substrate materials. In contrast, metamorphic GaAsP is needed as a top junction on Si for high-efficiency, low- cost applications. I will discuss how control over extended defects in these materials led to our demonstration of high open-circuit voltage InGaP and GaAsP cells on both GaAs and GaP substrates.

Next, I will discuss the strain-driven growth and luminescence properties of InGaAs quantum dots (QDs) on GaP. Since GaP is nearly lattice-matched to Si, these dots represent a new approach to efficient light emission on Si. Results on incorporation of InGaAs/GaP QDs into light-emitting diodes and photonic crystal cavities will be presented. The third topic is my group’s recent discovery that dislocation-free, tensile-strained nanostructures can be grown on (110) and (111) substrates. This result is unusual, since self-assembled island growth is typically driven by compressive strain on the (001) surface. I will present our analysis of these findings in terms of dislocation kinetics, as well as new results on tensile-strained GaAs QDs grown on In0.52Al0.48As/InP(110).

Biography:

Dr. Minjoo Larry Lee received the Sc.B. with honors in materials science and engineering from Brown University, Providence, RI in 1998 and the Ph.D. in electronic materials from the Massachusetts Institute of Technology (MIT), Cambridge, MA in 2003. From 2003 to 2006, he was a Postdoctoral Researcher with the Microsystems Technology Laboratory at MIT. From 2006-2007, he was with the Center for Thermoelectrics Research at RTI International in Durham, NC, and in 2008 he joined Yale University in New Haven, CT as an assistant professor of electrical engineering. He is the author or coauthor of over 80 technical papers and refereed conference proceedings and holds seven patents. He and his students have received numerous recognitions including: the DARPA Young Faculty Award, NSF CAREER award, the MRS gold award for graduate student research, the IEEE EDS George E. Smith award, and the North American MBE conference best student paper prize. In 2012, he was named Lange Lecturer in Materials at the University of California Santa Barbara in recognition of “outstanding contributions to strain engineered semiconductor materials”.


Postponed -- This colloquium will be rescheduled for a later date.


Dr. Jason T. Stauth, Dartmouth College

Wednesday, October 31, 2012 - 10:00am - 12:00pm

CoRE Building Lecture Hall

Photovoltaic Energy: A Circuits and Systems Perspective

Abstract:

The viability of photovoltaic energy has increased tremendously in the last decade as new manufacturing capacity (especially in China) has driven PV module costs to levels never thought possible. However, there remain challenges in achieving true grid-cost-parity for PV compared to other sources such as coal and natural gas. These challenges include balance of system components and system integration costs, both of which are now major focuses of the DOE. This talk will discuss PV systems from a general perspective, targeting audience members who have less exposure to the PV area. The basic configurations of PV systems will be presented from the cell, module, string, array, and power plant level. We will then drill down into the different architectures for the power management system including central inverter, micro-inverter, and other emerging architectures. New classes of multi-level DC-DC converter ‘partial-power processing’ circuits will be presented as next-generation solutions.

Biography:

Dr. Stauth received his MS and PhD degrees at University of California, Berkeley in 2006 and 2008 respectively. At U.C. Berkeley Dr. Stauth was affiliated with the Berkeley Wireless Research Center (BWRC) and the Power Electronics Research Group, studying under Prof. Seth Sanders. His research focused on high frequency power electronics and RF integrated circuits. In 2008 he co-founded QVSense, Inc. and operated as CTO until QVSense was acquired by Solar Semiconductor. He remained as Director of Hardware Engineering at Solar Semiconductor until 2011. Since 2011 he has been Assistant Professor at Dartmouth College.

Dr. Donglei Fan, University of Texas

Friday, October 26, 2012 - 10:00am - 12:00pm

CoRE Builidng 7th Floor Boardroom

Abstract:

Electric tweezers utilize DC and AC electric fields through voltages applied on patterned electrodes to manipulate nanoentities suspended in a liquid. Nanowires with a large aspect ratio are particularly suitable for use in electric tweezers for patterning, assembling, and manipulation. Despite operating in the regime of extremely small particle Reynolds number (of order 10−5), electric tweezers can manipulate nanowires with high precision to follow any prescribed trajectory, to rotate nanowires with controlled chirality, angular velocity and rotation angle. Electric tweezers have been applied to assemble nanowires into arrays of optical nanosensors, to determine the electronic properties of nanomaterials from their mechanical rotation in a noncontact and non-destructive manner, and to construct nanoelectromechanical system (NEMS) devices such as nanomotors and nano-oscillators. Electric tweezers have also been used to transport drug-carrying functionalized nanowires for cell-specific drug delivery.

Biography:

Dr. Donglei (Emma) Fan is an Assistant Professor in Department of Mechanical Engineering of the University of Texas at Austin since 2010. She received National Science Foundation CAREER award in 2012. Dr. Fan obtained her bachelor’s degree in chemistry from the Department of Intensive Instruction, an honor program for gifted youth, in Nanjing University, China, in 1999, and doctoral (2007) degrees in Materials Science and Engineering from the Johns Hopkins University (JHU). Prof. Fan’s work has spurred a series of publications on journals including Nature Nanotechnology, the Proceedings of National Academy of Science, Nano Today, Physical Review Letters, Applied Physics Letters, Advanced Materials, as well as three patent disclosures. Her work was widely reported by the academic news media such as Nature Nanotechnology, MRS Bulletin, PhysOrg.com, APS news, and had been selected multiple times by Virtual Journals of Nanoscale Science and Technology.


Dr. Sundeep Rangan, New York University - Polytechnic Institute

Wednesday, October 24, 2012 - 10:00am - 12:00pm

CoRE Building Room 701 Boardroom

Abstract

Sparsity has emerged as a powerful modeling concept in a wide range of signal processing and learning problems: Many high-dimensional objects admit a sparse representation in a suitable transform basis and the recent field of compressed sensing has provided efficient methods to exploit this sparse structure in estimation, dimensionality reduction and feature extraction. However, sparsity is generally not the only aspect of many practical inverse problems. This talk presents a powerful new class of algorithms called generalized approximate message passing (GAMP) that significantly extends the compressed sensing framework. The GAMP algorithm use Gaussian approximations of loopy belief propagation to reduce estimation problems on complex interconnected systems to smaller, local problems associated with the individual system components. For compressed sensing estimation, the GAMP method can incorporate arbitrary priors and nonlinearities, perform joint estimation of latent variables, and can exploit large classes of complex statistical relationships between variables. Moreover, for certain inverse problems with large random transforms, the GAMP method admits remarkably precise asymptotic performance characterizations with testable conditions for optimality -- even for problems that are non-convex and nonlinear. Applications are demonstrated in challenging identification problems in neuroscience and in optimization problems in wireless interference coordination. Joint work with Alyson Fletcher (UCSC), Phil Schniter (Ohio State), Ulugbek Kamilov (EPFL), Vivek K Goyal (MIT) and Lav Varshney (IBM).

Biography

Dr. Sundeep Rangan received the B.A.Sc. at the University of Waterloo, Canada and the M.Sc. and Ph.D. at the University of California, Berkeley, all in Electrical Engineering. He has held postdoctoral appointments at the University of Michigan, Ann Arbor and Bell Labs. In 2000, he co-founded (with four others) Flarion Technologies, a spin off of Bell Labs, that developed Flash OFDM, one of the first cellular OFDM data systems, and precursor to 4G cellular standards such as LTE and WiMax. Flarion grew to over 150 employees with trials worldwide. In 2006, Flarion was acquired by Qualcomm Technologies where Dr. Rangan was a Director of Engineering involved in OFDM infrastructure products. He joined the ECE department at NYU-Poly in 2010. His research interests are in wireless communications, signal processing, information theory and control theory.

Dr. Changho Suh, Korea Advanced Institute of Science and Technology

Wednesday, October 10, 2012 - 10:00am - 12:00pm

CoRE Building Lecture Hall

Abstract:

The computation problem in networks represents a task-oriented communication setup where receivers wish to compute functions of multiple sources. While the problem has received considerable attention with applications in sensor networks and cloud computing scenarios, only the simplest setting has been well understood thus far which consists of a single receiver wanting a linear function of the sources: It is shown that the cut-set bound is tight in the single-receiver case. Beyond this case, we are still lacking in our understanding. Even for the next simplest setting which includes another receiver with the same demand, it is not known whether the cut-set bound is tight.

In this talk, I will present our recent progress on the problem of multicasting a linear function to multiple receivers. What we have shown is twofold. First we find that a function-matching network structure enables higher computation rates than the separation scheme can provide. Secondly we show that unlike the single-receiver case, the cut-set bound is not tight when multicasting a function. In the process of deriving this conclusion, we characterize the computing capacity of a two-transmitter two-receiver linear deterministic network where both receivers want to decode a mod-2 sum of two independent Bernoulli sources generated at the two transmitters.

Furthermore, we extend our results to a more general setting, thus characterizing the computing capacity of a class of L transmitter L receiver networks in the limit of L. We believe our achievability and converse theorem can be used as key tools to address general computation problems in networks.

  
Biography

Dr. Changho Suh is an Assistant Professor in the Department of Electrical Engineering at Korea Advanced Institute of Science and Technology (KAIST) since 2012. He received the B.S. and M.S. degrees in Electrical Engineering from KAIST in 2000 and 2002 respectively, and the Ph.D. degree in Electrical Engineering and Computer Sciences from UC-Berkeley in 2011, under the supervision of Prof. David Tse. From 2011 to 2012, he was a postdoctoral associate at the Research Laboratory of Electronics in MIT. From 2002 to 2006, he had been with the Telecommunication R&D Center, Samsung Electronics. Prof. Suh received the David J. Sakrison Memorial Prize for outstanding doctoral research from the UC-Berkeley EECS Department in 2011, the Best Student Paper Award of the IEEE International Symposium on Information Theory in 2009 and the Outstanding Graduate Student Instructor Award in 2010. He was awarded several fellowships, including the Vodafone U.S. Foundation Fellowship in 2006 and 2007; the Kwanjeong Educational Foundation Fellowship in 2009; and the Korea Government Fellowship from 1996 to 2002.

Dr. Nicolas H. Younan, Professor and Chair, Mississippi State University

Wednesday, October 3, 2012 - 10:00am - 12:00pm

CoRE Building Lecture Hall

Title:
Scientific Challenges in Information Retrieval from Earth Observation (EO) Imagery

Abstract:

The ultimate goal of any Earth Observation (EO) system is to provide understanding. However, this understanding will often require expertise and/or data sources from globally distributed resources and will present some unique challenges for the local remote sensing analyst. To address these challenges, it is incumbent upon the global community to evolve and sustain a global observation network. These observations serve as the foundation for the models that are used to describe Earth processes. As this observational data accumulates in global archives new opportunities become available for knowledge discovery about the Earth system. However, access to these observational data is optimized for the science teams for whom the instruments were launched and access by operational users may be problematic. This presentation will lay out some of the Grand Challenges for those engineers and scientists involved in pattern recognition in the Earth remote sensing arena. It describes the problem space for making local decisions and introduces the concept of contextual remote sensing. Answers will require addressing the multi-dimensional aspects of the EO imagery – hyper-spatial, hyper-spectral, hyper-temporal, and hyper sensors.

Biography:

Nicolas H. Younan is currently the Department Head and James Worth Bagley Chair of Electrical and Computer Engineering at Mississippi State University. He received the B.S. and M.S. degrees from Mississippi State University, in 1982 and 1984, respectively, and the Ph.D. degree from Ohio University in 1988. Dr. Younan’s research interests include signal processing and pattern recognition. He has been involved in the development of advanced image processing and pattern recognition algorithms for remote sensing applications, image/data fusion, feature extraction and classification, automatic target recognition/identification, and image
information mining.

Dr. Younan has published over 200 papers in refereed journals and conference proceedings. He has served as the General Chair and Editor for the 4th IASTED International Conference on Signal and Image Processing, Co-Editor for the 3rd International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, Guest Editor, Pattern Recognition Letters and IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS), and Co-Chair, 4th and 5th Workshop on Pattern Recognition for Remote sensing (PRSS). He is a senior member of IEEE and a member of the IEEE Geoscience and Remote Sensing society, serving on two technical committees: Data Fusion, and Data Archive and Distribution. He also served as the Vice Chair of the International Association on Pattern Recognition (IAPR) Technical Committee 7 on Remote Sensing (2008-2010).


Dr. Kamin Whitehouse, University of Virginia

Wednesday, September 26, 2012 - 10:00am - 12:00pm

CoRE Building Lecture Hall

Title:
The Rise of the Practical Smart Home

Abstract:

People spend 60% of their time in their homes, and the performance of a home affects every aspect of a person's life. As such, "smart homes" have real potential to help people better understand and manage aspects of their own lives, including their energy consumption, medical health, and family function. This talk will present a new smart home system that can detect who is in the home, which rooms they are in, and what they are doing in terms of water fixture and electrical fixture usage -- but without instrumenting the people or fixtures, and without using cameras, microphones, or the use of wearable tags or transmitters. A main goal of the system is to be affordable and easy to install: in production version, it is expected to cost less than a new television, and to be installed in minutes.

Biography:

Dr. Kamin Whitehouse works in the areas of wireless sensor networks, with a focus on applications in energy conservation. He is an associate professor in the Computer Science Department at the University of Virginia, is a Siebel scholar, and was awarded NSF CAREER award. He earned his BA and BS from Rutgers University and his MS and Ph.D. from UC Berkeley.


Dr. Kyung Ryu, IBM T.J. Watson Research Center

Thursday, September 20, 2012 - 10:00am - 12:00pm

new location: CoRE Building Room 701 Boardroom

ABSTRACT

It has been more than a decade since the Blue Gene project started in IBM Research. Blue Gene/Q, the latest and third generation of Blue Gene, is again at the top of the Supercomputer TOP500 and Green500 lists.

This talk will highlight the evolution of the Blue Gene technologies and its revolutionary impact on Sciences. I will also discuss the new challenges and directions of Supercomputing beyond Blue Gene.

BIOGRAPHY

Dr. Kyung Dong Ryu is Manager and Research Project Leader of the Exascale System Software Research Group at the IBM T.J. Watson Research Center. Since 2004, he has led several research projects in High Performance Computing, Cloud Computing, Resilient HA Cluster, End-to-End System Performance Optimization. He had also led the scalable system management project for datacenters, advancing IBM’s systems management products, for which he received an Outstanding Technical Achievement Award from IBM. Before joining IBM Research, he was an Assistant Professor at the Arizona State University (2001-2004), where his research focused on PC Grid and Operating Systems for High Performance Computing. As a faculty member, he was awarded NSF grants and led several industrial research projects funded by the Research Consortium with Intel and Motorola. He published over 40 papers in premier international conferences and journals, including SC, ICS, IPDPS, ICDCS, TPDS, Eurosys, and ISCA. He received M.S. and Ph.D. in 1998 and 2001, respectively, from the University of Maryland, College Park, in Computer Science.


Prof. Janne Lindqvist, Rutgers University, WINLAB

Wednesday, September 12, 2012 - 10:00am - 12:00pm

CoRE Building Lecture Hall

Abstract

Many location-sharing systems have been developed over the past 20 years, but only recently have these systems started to be adopted by consumers. In this talk, we will discuss our work on understanding users and their use of location-sharing applications, and how people manage their privacy with real applications.

We will also introduce some of our ongoing research using location information to combat distracted driving and talk about crowdsourcing for understanding privacy and creating social connections between people.

____________________________________________________________________________________

Biography

Janne Lindqvist is an Assistant Research Professor at WINLAB/ECE, Rutgers University. Prior to Rutgers, Janne was a post-doc with the Human-Computer Interaction Institute at Carnegie Mellon University. Janne received his M.Sc. degree in 2005 and D.Sc. degree in 2009, both in Computer Science and Engineering from Helsinki University of Technology, Finland.

He works at the intersection of mobile computing, systems security and human-computer interaction. Before joining the academia, Janne co-founded a wireless networks company, Radionet, which was represented in 24 countries before being sold to Florida-based Airspan Networks in 2005.

During his first year at Rutgers, Janne was awarded three NSF awards totaling ca. $1.3 million.


Professor Ness B. Shroff, Ohio Eminent Scholar in Networking and Communications
Chaired Professor of ECE and CSE

Wednesday, April 25, 2012 - 10:00am - 12:00pm

CoRE Building Lecture Hall

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.


Professor Dario Pompili
Dept ECE, Rutgers University

Wednesday, April 18, 2012 - 10:00am - 12:00pm

CoRE Building Lecture Hall



Abstract:

Mobile platforms are becoming the predominant medium of access to Internet services due to the tremendous increase in their computation and communication capabilities. However, enabling applications that require real-time in-the-field data collection and processing using mobile platforms is still challenging due to i) the insufficient computing capabilities and unavailability of complete data on individual devices and ii) the prohibitive communication cost and response time involved in offloading data to remote centralized computing resources such as cloud datacenters.

This talks presents a novel resource provisioning framework for organizing the heterogeneous sensing, computing, and communication capabilities of static and mobile devices in the vicinity in order to form an elastic resource pool – a hybrid static/mobile computing grid. This local computing grid can be harnessed to enable innovative data- and compute-intensive mobile applications such as ubiquitous context-aware health and wellness monitoring of the elderly, distributed rainfall and flood-risk estimation, distributed object recognition and tracking, and content-based distributed multimedia search and sharing.

In order to address challenges such as the inherent uncertainty in the hybrid grid (in terms of network connectivity and device availability), a role-based resource-provisioning framework imparted with autonomic capabilities (self-organization, self-optimization, and self-healing) is proposed.

Biography:

Dario Pompili joined as Assistant Professor the faculty of the Department of Electrical and Computer Engineering (ECE) at Rutgers University in 2007, where he is the Director of the Cyber Physical Systems Laboratory (CPS Lab). He is also co-directing the Cloud and Autonomic Computing (CAC) Center, an NSF multi-institution research center funded by the I/UCRC program.

He received a Ph.D. in ECE from the Georgia Institute of Technology in 2007 after working at the Broadband Wireless Networking Laboratory (BWN-Lab). In 2005, he was awarded Georgia Institute of Technology BWN-Lab Researcher of the Year for “outstanding contributions and professional achievements". He had previously received his “Laurea” (integrated B.S. and M.S.) and Doctorate degrees in Telecommunications Engineering and System Engineering from the University of Rome “La Sapienza,” Italy, in 2001 and 2004.

His research interests include wireless sensor networks, underwater acoustic communication and coordination of underwater vehicles, green computing, and network optimization and control. He is author of many influential research articles on these topics. He serves on the editorial board of Ad Hoc Networks (Elsevier) Journal and on the technical program committee of several leading conferences on networking such as INFOCOM, MASS, SECON, GLOBECOM, ICC. In 2011, he received the NSF CAREER award for his work on underwater multimedia acoustic communication and the Rutgers/ECE Outstanding Young Researcher award. He has recently won a Young Investigator Program (YIP) grant from the ONR, one of only 26 awarded nationwide in 2012, for his proposal titled “Investigating Fundamental Problems for Real-time In-situ Data Processing in Heterogeneous Mobile Computing Grids.” He is member of the IEEE Communications Society and the ACM.


Professor Shantenu Jha, Department of Electrical & Computer Engineering,
Rutgers University

Wednesday, April 11, 2012 - 10:00am - 12:00pm

CoRE Building Lecture Hall

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.

Professor Jha is writing a book on "Abstractions for Distributed Applications and Systems: A Computational Science Perspective". Jha seeks fearless and revolutionary young minds to join the RADICAL (thinking) group! Away from work, Jha tries middle-distance running and biking, tends to be an economics-junky, enjoys reading and writing random musings and tries to use his copious amounts of free time with a conscience.


Professor Waheed U. Bajwa, Department of Electrical & Computer Engineering,
Rutgers University

Wednesday, April 4, 2012 - 10:00am - 12:00pm

CoRE Building Lecture Hall

Abstract:

The problem of model selection arises in a number of statistics and signal processing applications, such as subset selection in linear regression, estimation of structures in graphical models, and signal denoising. In this talk, we introduce a simple algorithm, termed one-step thresholding (OST) algorithm, for model-order agnostic model selection in linear inference problems. We utilize two geometric measures of coherence, namely, worst-case coherence and average coherence, among the columns of a design matrix to provide an in-depth analysis of OST for model selection. One of the key insights offered by the ensuing analysis is that OST can successfully carry out model selection even when methods based on convex optimization such as the lasso fail due to the rank deficiency of the submatrices of the design matrix. In addition, we show that OST has the ability to perform near-optimally for a number of generic (random or deterministic) matrices as long as the design matrix satisfies conditions that are easily computable in polynomial time -- an area of great interest in applications such as genetic biomarker identification using gene expression data.

Biography:

Waheed U. Bajwa received BE (with Honors) degree in electrical engineering from the National University of Sciences and Technology, Pakistan in 2001, and MS and PhD degrees in electrical engineering from the University of Wisconsin-Madison in 2005 and 2009, respectively. He was a Postdoctoral Research Associate in the Program in Applied and Computational Mathematics at Princeton University from 2009 to 2010, and a Research Scientist in the Department of Electrical and Computer Engineering at Duke University from 2010 to 2011. He is currently an Assistant Professor in the Department of Electrical and Computer Engineering at Rutgers University. His research interests include high-dimensional inference and inverse problems, compressed sensing, statistical signal processing, wireless communications, and applications in biological sciences, complex networked systems, and radar & image processing.

Dr. Bajwa was affiliated with Communications Enabling Technologies, Pakistan – the research arm of Avaz Networks Inc., Irvine, CA (now Quartics LLC) – from 2000-2003, with the Center for Advanced Research in Engineering, Pakistan during 2003, and with the RF and Photonics Lab of GE Global Research, Niskayuna, NY during the summer of 2006. He received the Best in Academics Gold Medal and President's Gold Medal in Electrical Engineering from the National University of Sciences and Technology (NUST) in 2001, and the Morgridge Distinguished Graduate Fellowship from the University of Wisconsin-Madison in 2003. He was Junior NUST Student of the Year (2000), Wisconsin Union Poker Series Champion (Spring 2008), and President of the University of Wisconsin-Madison chapter of Golden Key International Honor Society (2009). He served as a Guest Associate Editor for a special issue of Elsevier Physical Communication Journal on “Compressive Sensing in Communications” (2010-2011). He is currently a member of the IEEE, Pakistan Engineering Council, and Golden Key International Honor Society.


Dr. Stephen Weston
JP Morgan

Monday, April 2, 2012 - 10:00am - 12:00pm

CoRE Building Lecture Hall

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.


Professor Jie Wu,
Department of Computer & Information Sciences,
Temple University

Wednesday, March 21, 2012 - 10:00am - 12:00pm

CoRE Building Lecture Hall

Abstract

A paramount concern in dynamic wireless networks is efficient utilization of limited resources. The dynamic nature of wireless networks makes it difficult to use limited resources in a cost-efficient way. The traditional single-utility model, such as link quality, is inadequate for addressing this problem. In this talk, we discuss a composite utility model and use the routing problem in dynamic wireless networks as its application. Specifically, we integrate cost and link quality into a single network utility metric together with the benefiit of successful delivery of a routing packet to evaluate routing optimality. An efficient algorithm design, both centralized and distributed, is presented. Finally, several extensions to the basic model are discussed.

Biography

Jie Wu is chair and professor in the Department of Computer and Information Sciences at Temple University. Prior to joining Temple University, he was a program director at the National Science Foundation. His research interests include: wireless networks, mobile computing, routing protocols, fault-tolerant computing, and interconnection networks. He has published more than 550 papers in various journals and conference proceedings. He serves in the editorial boards of IEEE Transactions on Computers and Journal of Parallel and Distributed Computing. Dr. Wu was also general co-chair for IEEE MASS 2006, IEEE IPDPS 2008, and DCOSS 2009 and is the program co-chair for IEEE INFOCOM 2011. He has served as an IEEE Computer Society distinguished visitor. Currently, he is the chair of the IEEE Technical Committee on Distributed Processing (TCDP), an ACM distinguished speaker and a Fellow of the IEEE. Dr. Wu is the recipient of 2011 China Computer Federation (CCF) Overseas Outstanding Achievement Award.


Professor Jeffrey Walling

Department of Electrical & Computer Engineering,
Rutgers University

Wednesday, March 7, 2012 - 10:00am - 12:00pm

CoRE Building Lecture Hall

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.


Professor Steven Weber, Electrical & Computer Engineering
Drexel University

Wednesday, February 29, 2012 - 10:00am - 12:00pm

CoRE Building Lecture Hall

Abstract: Transmission capacity (TC) is a performance metric for wireless networks that measures the spatial intensity of successful transmissions per unit area, subject to a constraint on the permissible outage probability (where outage occurs when the SINR at a receiver is below a threshold). I present a unified treatment of the TC framework that has been developed over the past decade. The mathematical framework underlying the analysis is stochastic geometry: Poisson point processes model the locations of interferers, and (stable) shot noise processes represent the aggregate interference seen at a receiver. I first present TC results (exact, asymptotic, and bounds) on a simple model in order to illustrate a key strength of the framework: analytical tractability yields explicit performance dependence upon key model parameters. I then present enhancements to this basic model --- channel fading, variable link distances, and multi-hop. Time permitting, I will discuss four network design case studies well-suited to TC: i) spectrum management, ii) interference cancellation, iii) signal threshold transmission scheduling, and iv) power control.

Bio:

Steven Weber received his B.S. degree in 1996 from Marquette University in Milwaukee, WI, and his M.S. and Ph.D. degrees from The University of Texas at Austin in 1999 and 2003 respectively. He joined the Department ofElectrical and Computer Engineering at Drexel University in 2003 where he is currently an associate professor. His research interests are centered around mathematical modeling of computer and communication networks, specifically streaming multimedia and ad hoc networks.


Professor Jaeseok Jeon
Department of Electrical & Computer Engineering
Rutgers University

Wednesday, February 22, 2012 - 10:00am - 12:00pm

CoRE Building Lecture Hall



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.


Dr. Yuanyuan Yang, Dept. ECE, Stony Brook University

Wednesday, December 14, 2011 - 10:00am - 12:00pm

Core Building Lecture Hall

Abstract

In this talk, we consider a wireless sensor network that consists of a large number of sensors and a limited number of mobile data collectors. In such a network, mobile collectors take over the burden of routing from sensors, roaming over the
sensing area and collecting data from nearby sensors via short-range wireless communications. We present a series of efficient mobile data gathering schemes in such sensor networks, which aim to prolong network lifetime and shorten data gathering latency.

Moving path planning with multi-hop relays. We propose a moving path planning algorithm by adopting a divide and conquer method, which recursively determines a turning point on the path. The moving path of the mobile collector is planed dynamically based on the distribution of sensors, and load balancing among sensors is performed along with the moving path planning to prolong network lifetime.

Single-hop data gathering. To achieve uniform energy consumption among sensors, in this scheme, the mobile collector is scheduled to traverse the transmission range of each sensor such that data from each sensor can be collected via single-hop transmission. However, this approach typically results in significantly increased latency due to the low moving velocity of the mobile collector. Hence, we focus on minimizing the length of a data gathering tour by formulating it into an
optimization problem. A heuristic algorithm is proposed to provide a practically good solution to the problem.

Mobile data gathering with controlled mobility and SDMA technique. In this scheme,we apply the latest physical layer technique, Space-Division Multiple Access (SDMA), to sensor networks, which enables multiple sensors to upload data
simultaneously to the mobile collector so that data uploading time can be greatly shortened. To better enjoy the benefit of SDMA, mobile collector may have to visit some specific locations where more sensors are compatible, which may adversely prolong the moving tour. We propose an optimal solution that minimizes the data gathering latency by exploring a tradeoff between the shortest moving tour and the full utilization of SDMA.

Bounded relay hop mobile data gathering scheme. In this scheme, we study the inherent tradeoff between energy saving and data gathering latency of the mobile data gathering in sensor networks, by achieving a balance between the relay hop count of local data aggregation and the moving tour length of the mobile collector. We propose a polling-based mobile collection approach and formulate it into an optimization problem. Specifically, a subset of sensors are selected as polling points that buffer the locally aggregated data and upload the data to the mobile collector when it arrives. In the meanwhile, when sensors are affiliated with these polling points, it is guaranteed that the relaying of any packet is bounded within a given number of hops.

Biosketch

Dr.Yuanyuan Yang is currently a Full Professor of Electrical & Computer Engineering and Computer Science at Stony Brook University, and the Director of Communications and Devices Division at New York State Center of Excellence in Wireless and Information Technology (CEWIT). She received her PhD degree in computer science from Johns Hopkins University, Baltimore, Maryland, in 1992. Dr. Yang's research interests include interconnection networks, wireless/mobile networks, optical networks, high-speed networks, multicast communication and parallel and distributed
computing systems. She has authored or coauthored more than 230 research articles in leading refereed journals and conferences with over 60 papers published in IEEE Transactions on these topics. She is also an inventor/co-inventor of six U.S. patents in the area of interconnection networks.

Dr. Yang is currently an Associate Editor for the IEEE Transactions on Computers and a Subject Area Editor for the Journal of Parallel and Distributed Computing. She has served as an Associate Editor for IEEE Transactions on Parallel and Distributed Systems. She has served as a distinguished visitor of IEEE Computer Society. She received an IEEE Region 1 Award for ``significant contributions in multicast switching networks'' in 2002, and a Best Paper Award on optical interconnects at the 18th IEEE International Parallel and Distributed Processing Symposium (IPDPS) in 2004. She has served as a general chair, program chair or vice chair for several major conferences and a program committee member for numerous conferences. She was elected as an IEEE Fellow in 2009 "for contributions to parallel and distributed computing systems." More information about her and her research can be found at http://www.ece.sunysb.edu/~yang.


Dr. Anant Madabhushi, Dept. of Biomedical Engineering, Rutgers University

Wednesday, November 30, 2011 - 10:00am - 12:00pm

TBD

“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.


Dr. Irina Rish, IBM Watson

Canceled

Monday, November 28, 2011 - 10:00am - 12:00pm

Dr. Olgica Milenkovic, Dept ECE, University of Illinois Urbana- Champaign

Wednesday, November 16, 2011 - 10:00am - 12:00pm

Core Building Lecture Hall

ABSTRACT

Rank aggregation is the problem of combining multiple candidate rankings into one list that best reflects the candidates' standing as a whole. Rank aggregation has many applications, in fields as diverse as bioinformatics, coding theory and social sciences.

Mathematically, the rank aggregation problem can be formulated as finding a permutation that represents the ``centroid'' of a set of permutations - i.e., a permutation that minimizes a given average distance function from the given set of permutations. The main issue arising in such aggregation problems is to identify distance functions that are scalable, flexible and easy to compute.
So far, no solutions that have these desirable properties were proposed.

We introduce a new class of cost-constrained permutation metrics that can be approximated within a constant in polynomial time. The cost functions are based on average transposition distances and for costs that have a tree-metric form, the presented algorithms are exact. To prove the optimality of the distance computation procedure, we use Menger's theorem and graphical representations of permutations.

We conclude the talk by describing a number of applications of the novel distance metric in ``collaborative rank aggregation'' and coding for multilevel flash memories.
__________________________________________________________________________________________

BIOGRAPHY

Olgica Milenkovic received a MSc degree in mathematics and PhD degree in electrical engineering from the University of Michigan, Ann Arbor, in 2001 and 2002, respectively. From 2002 until 2006 she was with the faculty of University of Colorado, Boulder. In 2006, she was a visiting professor at the University of California, San Diego Center for Information Theory and Application. In 2007, she joined University of Illinois, Urbana-Champaign were she currently holds the position of associate professor. Her research interests are in algorithms, bioinformatics, coding theory, combinatorics and signal processing.

Olgica Milenkovic is a recipient of the NSF Career Award, the DARPA Young Faculty Award and a number of best conference paper awards. She currently serves as Associate editor in the Transactions on Signal Processing and the Transactions on Information Theory.

Dr. Bin Liu, Tsinghua University, China

Friday, November 11, 2011 - 10:00am - 12:00pm

Core Buliding - Lecture Hall

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.


Dr. Richard Frenkiel, WINLAB, Rutgers University

Wednesday, November 9, 2011 - 10:00am - 12:00pm

CoRE Building, Board Room 701

Abstract

Thirty years ago, most large companies had pension plans that promised retirees a "defined" pension-- usually about 1% of a person's final salary for each year worked. Someone with 40 years of service would therefore retire with about 40% of their final salary, plus another 20% or so from Social security. Some pensions even provided cost-of-living adjustments. This allowed a modest lifestyle in retirement or, with some savings, a comfortable and attractive lifestyle. In particular, these plans guaranteed income for life, at a time when people were retiring earlier and living longer.

From the employer's viewpoint, those "defined benefit" plans represented a substantial liability that could escalate sharply in a time of inflation, and as life expectancies increased. As a result, most employers abandoned these "promises to pay" as too expensive and risky in a competitive world. The "defined benefit" pension is now almost extinct, and a successful life now requires some new skills in planning and investing.

Savings plans like the 401K (and other similar retirement savings accounts) are essential to this task. They defer income taxes on "contributions" (money that is put in), and on growth (money that is earned in the account), until the money is removed. Additionally, some employers also "match" a fraction of the employee's contribution. Compared to saving without a 401K, the tax advantage and employer match can easily triple the "effective pension" that can be achieved (the amount of money a person can eventually take out annually in retirement). Even without an employer match, the "effective pension" can be doubled by the delayed tax alone, so there is a strong incentive to participate in whatever type of plan is available. Those who contribute a reasonable amount to these plans, and who invest the money in their plans intelligently, can look forward to retiring relatively early into lives that are interesting, secure and comfortable. Those who fail to contribute, or who invest foolishly, will work longer than they want to and spend their last years in relative poverty. For the new graduate with a first job, these issues may seem far off and more immediate concerns may seem more important. Frequently, action gets postponed, and with each year of delay the desired result becomes harder to achieve.

In this lecture, we will use a simple planning spreadsheet and some basic financial data to explore the issues of how much to save and how to invest those savings. There is no single answer to these questions, of course. Some will wish to retire earlier or live more expensively in retirement. Some will be willing to take greater risks to achieve their goals. The objective of the lecture is for the student to understand what is possible, and how such lifestyle goals are reflected in the overall plan.

BIOSKETCH

Dick Frenkiel was born more than a half-century ago, in a small town called Brooklyn. He attended Tufts University and Rutgers University, emerging with degrees in Mechanical Engineering and a deceptive aura of competence. Soon after joining Bell Laboratories in 1963, he was mistaken for an electrical engineer of similar height and moved into cellular systems engineering, where for sixteen years he did little serious harm.

During the late 1960's. Dick was an author of AT&T's cellular system proposal to the FCC. After an obligatory "growth experience" at corporate headquarters, during which he acquired several suits, he returned to Bell Labs, where he became head of systems engineering for AMPS, the first cellular system in the US. He invented a method for efficient and low-cost cell-splitting, and served on the EIA committee which defined the first cellular standards to be used in the United States.

For Dick, the joy of seeing AT&T's first cellular service in Chicago was somewhat diminished when the company was torn apart by the government and excluded from the cellular business. While not responsible for this calamity, he exiled himself to the lowly world of consumer electronics. He became head of R&D for AT&T's cordless telephone business unit, and led a team that developed cordless telephones, some of which actually worked. He was also responsible for the first manufacture of these telephones in Singapore and Hong Kong, where he acquired several additional suits at attractive prices.

Dick retired from AT&T in 1993, and spent many happy years at WINLAB, the Wireless Information Networks Laboratory here at Rutgers. In 1999, he served as mayor of Manalapan Township in New Jersey and was not indicted. With Professor Narayan Mandayam he teaches a multi-disciplinary course in business strategy in the wireless industry.

For his work in wireless, Dick has received the National Medal of Technology, the Alexander Graham Bell Medal and the Industrial Research Institute Achievement Award. He is a member of the National Academy of Engineering, a New Jersey Inventor of the Year, and a Fellow of Bell Labs and the IEEE.



Dr. Zhi-Quan Luo

Friday, November 4, 2011 - 2:00pm - 4:00pm

CoRE Board Room 701

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.


Dr. Wei Jiang, Rutgers University, Dept. of Electrical & Computer Engineering

Wednesday, November 2, 2011 - 10:00am - 12:00pm

CoRE Board Room 701

Abstract

Silicon photonics offers a low-cost platform for building large-scale photonic devices and circuits, potentially replicating the success of silicon microelectronics in photonics. Photonic crystal nanostructures provide novel physical mechanisms, such as the slow-light effect and superprism effect, to reduce the size and improve the performance of silicon photonic devices. This talk will review our recent work on silicon-compatible waveguides, including slow-light photonic crystal waveguides, for use as on-chip optical delay lines. Particularly, some fundamental physical issues of photonic crystal waveguides such as slow-light loss will be addressed. Optical delay lines have applications in phased array antennas, optical signal processing, and optical modulation. It will be shown that the current slow-light loss levels are sufficient for some applications, whereas challenges remain in other applications. This talk will also review our work on dual racetrack silicon micro-resonators for quadrature amplitude modulation. Potential applications of these device components in optical communications, optical interconnects, laser beam steering, and optical signal processing will be discussed.

Bio sketch

Wei Jiang is an assistant professor in the Department of Electrical and Computer Engineering of Rutgers, the State University of New Jersey. He received his B.S. degree in physics from Nanjing University, Nanjing, China, in 1996, and his M.A. degree in physics and his Ph.D. degree in electrical and computer engineering from the University of Texas, Austin, in 2000 and 2005, respectively. His research interests encompass silicon photonics, photonic crystals, nanophotonics, and their applications in various optoelectronic systems.

Dr. Jeyanandh Paramesh, Carnegie Mellon University

Wednesday, October 19, 2011 - 10:00am - 12:00pm

CoRE Board Room 701

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

Dr. Jeong Bong Lee
University of Texas at Dallas

Location: Computer Science Seminar Room CoRE-301

Friday, October 14, 2011 - 10:00am - 12:00pm

Computer Science Seminar Room CoRE-301

Photonic crystals are ultra-compact highly integrated nano scale structures which demonstrated the possibility of generating, manipulating, processing, transmitting and detecting light. However, most photonic crystal devices are “passive” structures without any means of external on-demand control. Adding tunability to the photonic crystals would greatly expand their application areas and enable unforeseen new application areas. MEMS/NEMS technologies are ideally positioned to provide a wide variety of unprecedented radical options of tunability to the passive photonic crystal devices as they can be co-integrated with photonic crystals. We have recently reported MEMS-enabled mechanically tunable and thermally tunable photonic crystals. Various applications and current status of development of such tunable photonic crystals will be discussed.

Speaker Bio:

Dr. Jeong-Bong (JB) Lee received the Ph.D. degree from Georgia Tech, Atlanta, Georgia in 1997. In 2001, he joined the Electrical Engineering Department at UTD where he is now a full professor. His current research interests include MEMS and nanophotonics for biomedical and photonics applications. He received the NSF CAREER AWARD in 2001. He is currently serving as an editorial board member for Micromachines journal. He has served as a program committee member for many international conferences including Transducers 2011 Conference as a member of executive program sub-committee. He also served as a member of external advisory board for the Microsystems division at the Sandia National Laboratories in 2007. He has five U.S. patents, more than 45 journal papers and 138 conference papers published.

Dr. K. Venkatesh Prasad
Ford Motor Company

Wednesday, September 28, 2011 - 10:00am - 12:00pm

CoRE Building Auditorium

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.

Professor Adrian Perrig
Carnegie Mellon University

Tuesday, May 3, 2011 - 10:00am - 12:00pm

CoRE Auditorium

"SCION: Scalability, Control, and Isolation on Next-Generation Networks" by Prof. A. Perrig, Carnegie Mellon University

We present the first Internet architecture designed to provide route control, failure isolation, and explicit trust information for end-to-end communications. SCION separates ASes into groups of independent routing sub-planes, called trust domains, which then interconnect to form complete routes. Trust domains provide natural isolation of routing failures and human misconfiguration, give endpoints strong control for both inbound and outbound traffic, provide meaningful and enforceable trust, and enable scalable routing updates with high path freshness. As a result, our architecture provides strong resilience and security properties as an intrinsic consequence of good design principles, avoiding piecemeal add-on protocols as security patches. Meanwhile, SCION only assumes that a few top-tier ISPs in the trust domain are trusted for providing reliable end-to-end communications, thus achieving a small Trusted Computing Base. Both our security analysis and evaluation results show that SCION naturally prevents numerous attacks and provides a high level of resilience, scalability, control, and isolation.

Bio
Adrian Perrig is a Professor in Electrical and Computer Engineering, Engineering and Public Policy, and Computer Science at Carnegie Mellon University. Adrian serves as the technical director for Carnegie Mellon's Cybersecurity Laboratory (CyLab). He earned his Ph.D. degree in Computer Science from Carnegie Mellon University, and spent three years during his Ph.D. degree at the University of California at Berkeley. He received his B.Sc. degree in Computer Engineering from the Swiss Federal Institute of Technology in Lausanne (EPFL). Adrian's research revolves around building secure systems and includes network security, trustworthy computing and security for social networks. More specifically, he is interested in trust establishment, trustworthy code execution in the presence of malware, and how to design secure next-generation networks.

Dr. Patrick Flandrin
Department of Ecole Normale Superieure de Lyon, France

Friday, April 29, 2011 - 2:00pm - 3:00pm

7th Floor Board Room, CoRE Building

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.

Professor Milica Stojanovic
Northeastern University

Wednesday, April 27, 2011 - 10:00am - 12:00pm

CoRE Auditorium

"Underwater Sensor Networks: Random Access and Compressive Sensing" by M. Stojanovic, Northeastern University

Wireless information transmission through the ocean is one of the enabling technologies for the development of future ocean-observation systems, whose applications range from oil industry to aquaculture and include gathering of oceanographic data, pollution control, climate recording, and transmission of images from remote sites. Underwater wireless communications are usually established using acoustic waves, since electro-magnetic waves propagate only over very short distances. However, acoustic communications are limited by three factors: low bandwidth, low speed of sound, and poor quality of the physical link. These constraints yield a difficult communication channel, while additional, system-level constraints come from the limited battery supply (re-charging is difficult underwater) and the half-duplex operation of existing acoustic modems. For networks that are deployed for long-term monitoring of environmental phenomena, it is crucial to design an efficient data gathering scheme that prolongs the system’s life-time. To this end, we exploit the sparse nature of the monitored field and design a random access / compressive sensing (RACS) scheme in which the sensors transmit at random to a fusion center which then reconstructs the field. We provide an analytical framework for system design that captures packet collisions due to random access, as well as packet errors due to communication noise. Through analysis and examples, we demonstrate that recovery of the field can be attained using only a fraction of the resources (energy per bit, bandwidth) used by a conventional TDMA network, while employing a scheme that is simple to implement, requires no synchronization or scheduling, and no downlink feedback.

Bio
Milica Stojanovic graduated from the University of Belgrade, Serbia, in 1988, and received the M.S. and Ph.D. degrees in electrical engineering from Northeastern University, Boston, MA, in 1991 and 1993. After a number of years with the Massachusetts Institute of Technology, where she was a Principal Scientist, she joined the faculty of Electrical and Computer Engineering Department at Northeastern University in 2008. She is also a Guest Investigator at the Woods Hole Oceanographic Institution, and a Visiting Scientist at MIT. Her research interests include digital communications theory, statistical signal processing and wireless networks, and their applications to underwater acoustic communication systems. Milica is a Fellow of the IEEE and serves as an Associate Editor for the IEEE Journal of Oceanic Engineering and the IEEE Transactions on Signal processing.

Link to Dr. Stojanovic's presentation slides.

Professor Nader Engheta
University of Pennsylvania

Tuesday, April 5, 2011 - 10:00am - 12:00pm

Core Auditorium

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.

Flyer - Nader Engheta

Professor Philippe M. Fauchet
University of Rochester

Wednesday, March 23, 2011 - 10:00am - 12:00pm

CoRE Lecture Hall

Flyer - Philippe M. Fauchet

Dr. Ali H. Sayed
University of California Los Angeles

Monday, March 21, 2011 - 10:00am - 12:00pm

CoRE Auditorium

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.

Flyer - Ali Sayed

Professor Stojanovic
Northeastern University

Tuesday, March 15, 2011 - 12:23pm - Wednesday, March 16, 2011 - 12:23pm

CoRE 701 Boardroom

Professor Youngmoo Kim
Drexel University

Wednesday, March 2, 2011 - 10:00am - 12:00pm

CoRE Building room 301

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.

Flyer - Youngmoo Kim

Dr. Thomas Schneider
National Institutes of Health
Frederick, Maryland

Wednesday, February 23, 2011 - 1:00pm - 3:00pm

CoRE Lecture Hall

Thomas D. Schneider, Ph.D.
National Cancer Institute at Frederick
Gene Regulation and Chromosome Biology Laboratory
Molecular Information Theory Group

Wednesday, February 23, 2011 - 12:25pm

Core Auditorium

Professor Paul Oh
Drexel University

Wednesday, February 16, 2011 - 2:00pm - 4:00pm

CoRE Lecture Hall

Flyer - Paul Oh

Professor Tsuhan Chen
Cornell University, Dept ECE

Monday, December 6, 2010 - 2:00pm - 4:00pm

CoRE Lecture Hall

Flyer - Tsuhan Chen

Dr. Hubertus Franke
IBM T.J. Watson Research Center

Wednesday, December 1, 2010 - 10:00am - 12:00pm

CoRE Lecture Hall

Flyer - Hubertus Franke

Professor Xiaodong Wang
Columbia University

Wednesday, October 20, 2010 - 10:00am - 12:00pm

CoRE Lecture Hall

Flyer - Xiaodong Wang