Speaker: Professor Nils Torbjörn Ekman, Norwegian University of Science and Technology
Time: Friday September 7, 1:00 pm
Location: Room 10.099, 10th Floor, 2 MetroTech Center, Brooklyn
A common problem in testing of MIMO algorithms is the need of a sufficiently realistic channel model and simulator. To obtain a fast and simple MIMO-channel simulator we propose to use state space models based on the radio propagation from scattering clusters. The spatial scattering clusters result in angle of arrival/departure and time of arrival distributions that can be approximated by combinations of simple distributions. The spatial-temporal and spectral channel correlations caused by each cluster are approximated using correlated AR-processes. This renders the appropriate spatial-temporal-spectral channel correlation in the simulated channels. The method can be interpreted as a generalization of sinusoidal modeling with the addition of stochastic components.
Nils Torbjörn Ekman was born in Västerås, Sweden, in 1969. He received the M.Sc. degree in engineering physics in 1994 and the Ph.D. degree in signal processing in 2002, both from Uppsala University, Sweden. In 2006 he joined the Department of Electronics and Telecommunications at the Norwegian University of Science and Technology (NTNU) in Trondheim, Norway, as an Associate Professor. From 1997 to 1998 he was a visiting scientist at the Institute of Communications and Radio-Frequency Engineering, Vienna University of Technology, Vienna, Austria, on a Marie Curie Grant. From 1999 to 2002, he was visiting the Digital Signal Processing Group, University of Oslo, Norway. In 2002–2005, he made his postdoctoral studies at UniK, Norway. He just finished a one-year long sabbatical at NYU Poly. His current research interests include signal processing in wireless communications, scheduling of radio resources, and dynamic modeling, and prediction of radio channels. He is currently participating in projects on maritime radio, broadband radio access and cognitive radio, studying radio resource management and channel modeling.
Speaker: Professor Tony T. Lee, Shanghai Jiao Tong University
Time: Wednesday September 12, 11:00 am
Location: RH418, Rogers Hall, 6 MetroTech Center, Brooklyn
This paper explores the application of a new algebraic method of color exchanges to the edge coloring of simple graphs. Vizing’s theorem states that the edge coloring of a simple graph G requires either Δ or Δ+1 colors, where Δ is the maximum vertex degree of G. Holyer proved that it is NP-complete to decide whether G is Δ-edge-colorable even for cubic graphs. By introducing the concept complex colored edges, we show that the color-exchange operation of complex colors follows the same multiplication rules as quaternion. An initially Δ-edge-colored graph G allows variable-colored edges, which can be eliminated by color exchanges in a manner similar to variable eliminations in solving systems of linear equations. The problem is solved if all variables are eliminated and a properly Δ-edge-colored graph is reached. For a randomly generated graph G, we prove that our algorithm returns a proper Δ-edge-coloring with a probability of at least 1/2 in O(Δ|V| |E|^5 ) time if G is Δ-edge-colorable. Otherwise, the algorithm halts in polynomial time and signals the impossibility of a solution, meaning that the chromatic index of G probably equals Δ+1. The Δ-edge-coloring problem of bipartite graphs is completely solved. The best known algorithm for finding a proper Δ-edge-coloring of a bipartite graph runs in time O(|E|logΔ) . The running time of our algorithm for bipartite graphs is on the order of O(|E|log|V|). As for non-bipartite graphs, the only known result is 3-edge-coloring of cubic planar graphs. As Tait proved that the 3-edge-coloring problem of bridgeless cubic planar graphs is equivalent to the four color map problem, the newly improved proof of four-color theorem actually can give rise to a quadratic algorithm for finding proper 3-edge-coloring of cubic planar graphs. Thus, our approach is the first randomized algorithm for finding Δ-edge-coloring of general graphs.
Tony T. Lee received his BSEE degree from National Cheng Kung University, Taiwan in 1971, and his MS and PhD degrees in electrical engineering from Polytechnic University in New York, in 1976 and 1977, respectively. Currently, he is a Chair Professor at the Electronic Engineering Department of Shanghai Jiao Tong University. He was a Professor of Information Engineering at the Chinese University of Hong Kong from 1993 to 2010, and a Professor of Electrical Engineering at Polytechnic University of New York from 1991 to 1993. He was with AT&T Bell Laboratories, Holmdel, NJ, from 1977 to 1983, and Bellcore, currently Telcordia Technologies, Morristown, NJ, from 1983 to 1993. He is now serving as an Editor of the IEEE Transactions on Communications, and an area Editor of Journal of Communication Network. Tony is a fellow of IEEE and HKIE. He has received many awards including the 1989 Leonard G. Abraham Prize Paper Award from IEEE Communication Society, the 1999 Outstanding Paper Award from IEICE of Japan, and the 1999 National Natural Science Award from China.
Speaker: Professor Keren Bergman, Columbia University
Time: Thursday September 20, 11:00 am
Location: JAB674, Jacobs Academic Building, 6 MetroTech Center, Brooklyn
Performance scalability of computing systems built upon multicore architectures are becoming increasingly constrained by limitations in power dissipation, chip packaging, and the data throughput achievable by the on- and off-chip interconnection networks. Future performance gains are impeded by the challenges of an increasing portion of the power budget consumed by global communication among the processing cores. The power dissipation problem is further exacerbated for off-chip communication due to limited on-chip power budget and available I/O. These challenges have emerged as the key barriers to realizing the required memory bandwidths and system wide data movement. Recent advances in chip-scale silicon photonic technologies have created the potential for developing optical interconnection networks that offer highly energy efficient communications and significantly improve computing performance-per-Watt. This talk will examine the design and performance of photonic networks-on-chip architectures that support both on-chip communication and off-chip memory access in an energy efficient manner. Current challenges of inserting nanophotonic interconnect technologies in future computing systems will be discussed.
Keren Bergman is the Charles Batchelor Professor and Chair of Electrical Engineering at Columbia University where she also directs the Lightwave Research Laboratory (http://lightwave.ee.columbia.edu/). She leads multiple research programs on optical interconnection networks for advanced computing systems, data centers, optical packet switched routers, and chip multiprocessor nanophotonic networks-on-chip. Dr. Bergman holds a Ph.D. from M.I.T. and is a Fellow of the IEEE and of the OSA. She currently serves as the co-Editor-in-Chief of the IEEE/OSA Journal of Optical Communications and Networking.
Speaker: Rodrigo Alvarez and Lars Lindenmüller
Time: Thursday September 27, 11:00 am
Location: JAB674, Jacobs Academic Building, Six MetroTech Center, Brooklyn
Due to historical reasons, in Germany as well as in other European countries, most of the railway is electrified with a single phase 15 kV, 16.7 Hz overhead wire. This means in conventional traction systems that a very large and heavy input transformer is required. To reduce weight and increase the efficiency in traction applications several power electronics based solutions have been proposed. Amongst them is the so called medium frequency topology (or power electronic transformer). Key element of this topology is a high power, medium voltage series resonant converter (SRC), that provides an isolation barrier with a transformer operated at several kilohertz. Using HV-IGBTs here is especially challenging since the switching frequency is approximately 20 times higher than in other typical, hard switching, applications where these devices are employed. In the presentation, different ways to reduce the switching losses, as well as a method to optimize the converter in a given application (apart from traction, the SRC can be employed in applications such as high power offshore wind or back-to-back networks) are shown.
Rodrigo Alvarez born in Santiago, Chile, received the Electronic Eng. and M. Sc. degree in Power Electronics from the Universidad Técnica Federico Santa María (UTFSM), Valparaiso Chile, in 2006. In 2007 he joined the Power Electronics group at the Dresden Technical University, where he received the Dr.-Ing degree in Power Electronics in 2011. He is currently working as senior scientist with the Power Electronics group at the Dresden Technical University, leading several strategic power electronics research projects for low voltage high power and medium voltage applications.
Lars Lindenmüller received the Diploma degree in Electrical Engineering from the Technische Universität Dresden, Germany, in 2009. Since then he is with the Power Electronics group and is currently working towards his Ph.D. degree. His research interests include high power resonant converters, applications of HV-IGBTs, multilevel topologies and traction applications.
Speaker: Professor Michele Zorzi
Time: Thursday October 4, 11:00 am
Location: JAB674, Jacobs Academic Building, Six MetroTech Center, Brooklyn
Energy Harvesting (EH) is a new paradigm in Wireless Sensor Networks (WSNs): sensor nodes are powered by energy harvested from the ambient, rather than by non-rechargeable batteries, thus enabling a potentially perpetual operation of the WSN. However, Energy Harvesting poses new challenges in the design of WSNs, in that energy availability is random and fluctuates over time, thus calling for radically different energy management solutions. In this talk we investigate the following fundamental question: how should the harvested energy be managed to ensure optimal performance? First, we consider a sensor powered by EH which senses data of varying importance and reports them judiciously to a Fusion Center. Assuming that data transmission incurs an energy cost, our objective is to identify low-complexity policies that achieve close-to-optimal performance, in terms of maximizing the average long-term importance of the reported data. We first consider schemes that rely on the assumption of perfect knowledge of the amount of energy available in the battery. Subsequently, we investigate the design of operation policies that maximize the long-term reward under imperfect knowledge of the State-Of-Charge (SOC). Moreover, for both scenarios, we explore the impact of time-correlation in the EH process, showing that simple adaptation to the state of the EH process yields close-to-optimal performance, without requiring full knowledge of the SOC of the battery.
Michele Zorzi is a Professor at the Department of Information Engineering of the University of Padova. Prior to his current appointment, he was employed at the Politecnico di Milano, the University of Ferrara and the University of California at San Diego, with which he still has an active collaboration. He received a PhD in Electrical Engineering from the University of Padova in 1994. Michele was the EiC of the IEEE Wireless Communications magazine in 2003-2005, and the EiC of the IEEE Transactions on Communications in 2008-2011, and has served on the Editorial Boards of the top journals in his area of research and on the Organizing and Technical Program Committee for many international conferenced. He is an IEEE Fellow. His main research interests are in the area of wireless communications and networking, sensor networks and IoT, underwater communications and networks, and energy-efficient protocol design.
Speaker: Professor Chengmo Yang
Time: Thuesday October 9, 11:00 am
Location: Room 10.099, 10th Floor, 2 MetroTech Center, Brooklyn
While advances of semiconductor technology enable more and more cores to be integrated on a single chip, the underlying computational fabric is at the same time becoming increasingly unreliable. The transistors are pushed to operate near their quantum limit, raising an extraordinary challenge of guaranteeing application correctness in the face of elevated rate of transient, intermittent, and permanent errors. In such a highly unreliable environment, the challenge is not just to guarantee full fault resilience, but furthermore to provide resilience support in conjunction with the goals that designers already face, such as high performance, low power and low hardware cost.
To address this challenge, this talk presents two tightly-coupled techniques that detect hardware faults and recover from them within minimum amount of comparison and checkpointing operations. Only the instruction results that either influence the final program results or are needed during re-execution are compared for fault detection. Meanwhile, the main memory is protected against contamination by execution faults, thus drastically reducing the checkpointing overhead. These two techniques can be implemented through a minimum hardware extension to the register file and the cache. Their ability of delivering full resilience within maximum efficiency will broaden the applicability of redundant execution to systems of tight power and resource constraints.
Dr. Chengmo Yang received a B.S. degree in Microelectronics from Peking University, China in 2003, a M.S. and a Ph.D. degree in Computer Engineering from the University of California, San Diego in 2005 and 2010, respectively. She is currently an assistant professor in the Department of Electrical and Computer Engineering at the University of Delaware. Her research interests lie in the broad areas of computer architecture and embedded systems, with a particular focus on the development of reliable and power-efficient multi/many core systems. She is currently recruiting Ph.D. students.
Speaker: Professor Qing Zhao
Time: Friday October 19, 1:30 pm
Location: JAB473, Jacobs Academic Building, Six MetroTech Center, Brooklyn
Since the first multi-armed bandit (MAB) problem posed by Thompson in 1933 for the application of clinical trials, MAB has developed into an important branch in stochastic optimization and machine learning and has found a wide range of applications in economics and finance, medicine, and industrial engineering. It has recently received increasing attention from the communications and networking research community for formulating and tackling the optimization of learning and activation in dynamic systems with unknown models. A mathematical abstraction of the MAB problems involves a player who can operate one of N arms at each time, with each yielding a random reward drawn from an unknown distribution when operated. The objective is an arm selection policy that minimizes the regret defined as the performance loss with respect to a genie who knows the reward model of each arm. In this talk, we present our recent results that extend the classic MAB theory in several directions: from exponential family of reward distributions to heavy tail reward distributions, from a single player to multiple distributed players, from i.i.d. reward models to restless Markov reward models, and from independent to correlated arms.
http://www.ece.ucdavis.edu/~qzhao/
Qing Zhao received the Ph.D. degree in Electrical Engineering in 2001 from Cornell University, Ithaca, NY. In August 2004, she joined the Department of Electrical and Computer Engineering at University of California, Davis, where she is currently a Professor. Her research interests are in the general area of stochastic optimization, decision theory, and algorithmic theory in dynamic systems and communication and social networks.
She received the 2010 IEEE Signal Processing Magazine Best Paper Award and the 2000 Young Author Best Paper Award from the IEEE Signal Processing Society. She holds the title of UC Davis Chancellor’s Fellow and received the 2008 Outstanding Junior Faculty Award from the UC Davis College of Engineering. She was a plenary speaker at the 11th IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 2010. She is also a co-author of two papers that received student paper awards at ICASSP 2006 and the IEEE Asilomar Conference 2006.
Speaker: Professor Daniel D. Lee
Time: Wednesday October 24, 11:00 am
Location: Room 10.099, 10th Floor, 2 MetroTech Center, Brooklyn
Planning and controlling robots with many degrees of freedom in complex environments is very challenging with real-time computational constraints. I will show how low-dimensional reductions can be used to solve high-dimensional motion trajectory optimizations. Our algorithm learns symmetries in the high-dimensional cost function to find an appropriate low-dimensional value function, in accordance with Noether's theorem in Lagrangian mechanics. This allows us to compute optimal trajectories with complexity less than the dimensionality of the naive configuration space. Applications of these methods will be shown on highly articulated arms and humanoid robots.
Daniel D. Lee is currently the Evan Thompson Term Chair, Raymond S. Markowitz Faculty Fellow, and Professor in the School of Engineering and Applied Science at the University of Pennsylvania. He received his B.A. in Physics from Harvard University in 1990, and his Ph.D. in Condensed Matter Physics from the Massachusetts Institute of Technology in 1995. Before coming to Penn, he was a researcher at Bell Laboratories, Lucent Technologies, in the Theoretical Physics and Biological Computation departments. He has received the NSF Career award and the University Lindback award for distinguished teaching; he was a fellow of the Hebrew University Institute of Advanced Studies in Jerusalem, an affiliate of the Korea Advanced Institute of Science and Technology, and has helped organize the US-Japan National Academy of Engineering Frontiers of Engineering symposium. At the GRASP Lab and as director of the University Transportation Center at Penn, his group focuses on understanding general computational principles in biological systems, and on applying that knowledge to build autonomous systems.
Speaker: Professor Robert Bitmead
Time: Thursday October 25, 11:00 am
Location: LC400, Dibner Building, Five MetroTech Center, Brooklyn
Internet congestion control is a specialized feedback control problem where, in TCP/IP, the feedback consists of acknowledgement, or ACK, packets and is used by the source computer to regulate input data rates. This situation is recast as a state estimation problem, where the state is that of a bottleneck router and consists of buffer space and competing traffic state elements. The state evolution is described by a Hidden Markov Model. Observability of this state from the source is then studied and the usual definition of observability found lacking for such stochastic system. A new definition is proposed, which reduces to the usual one in linear deterministic systems. For Hidden Markov Models however, this new definition sheds new light on the role of the feedback control law in maintaining observability and on the control performance price paid for adaptation in general.
Bob hails from Australia originally and was at the Australian National University for 17 years before coming to UCSD in 1999. He will officiate as a Field Umpire at the US National Championships of Australian Rules Football in Mason Ohio shortly before coming to PINYU. He is a Fellow of IEEE, of IFAC, and of the Australian Academy of Technological Sciences & Engineering. He works in Control Systems, Signal Processing and Telecommunications, with an interest in the areas of intersection. He is a regular consultant to industry in the areas of modeling, estimation, and control. He was Associate Vice-Chancellor for Academic Personnel at UCSD from 2006-2009 and brews his own beer.
Speaker: Professor Michail Maniatakos
Time: Thursday November 15, 11:00 am
Location: Silleck Lounge, Jacob Building, Six Metro Tech Center, Brooklyn
Ensuring quality, resilience, and trustworthiness of modern microprocessors is paramount to their ubiquitous deployment in contemporary applications. However, as microprocessors constitute the most complex integrated circuits, exhaustively analyzing their design and implementation in order to identify weaknesses that may jeopardize their robustness is infeasible. Toward devising realistically applicable solutions, this seminar explores the various trade-offs involved in developing and incorporating cost-effective robustness features. The ability to reason across layers, from transistors to architecture and from events to instructions, serves as the key to developing robustness enhancing solutions which extend beyond academic curiosity and become industrially relevant. Accordingly, effectiveness of the proposed methods will be demonstrated not only on academic microprocessor models, but also on commercial microprocessors (e.g., SUN SPARC, Intel Core).
Michail Maniatakos is an Assistant Professor of Electrical and Computer Engineering at New York University Abu Dhabi. He received a Ph.D. and M.Sc. in Electrical Engineering from Yale University as well as the B.S. and M.Sc. degrees in Computer Science and Embedded Systems from the University of Piraeus, Greece, in 2006 and 2007, respectively. His research interests include modern microprocessor robustness, hardware security and computer architecture. He is the recipient of the 2011 IEEE TTTC Gerald W. Gordon Award, as well as the winner of the 2011 Embedded Systems Challenge of the NYU-Poly Cyber-Security Awareness Week (CSAW).
Speaker: Doctor Ricardo L. de Queiroz
Time: Monday November 19, 11:00 am
Location: LC400, Dibner Building, Five MetroTech Center, Brooklyn
Video transmission usually demands large computational capacity, be it for compression, decompression or for other actions such as view synthesis and depth estimation. Mobile devices, in the other hand, typically possess less capable processors in order to save battery reserves. A few issues are discussed and results are presented on: scalable computing codecs and RDC optimization; Wyner-Ziv transcoders for real time transmission from mobile to mobile; mixed resolution video coding for reduced complexity; and free-viewpoint television architecture and resource allocation using mobile cameras and/or mobile receivers.
Dr. Ricardo L. de Queiroz received his Ph.D. degree from The University of Texas at Arlington in 1994. He joined the research staff at Xerox Corp. from 1994 to 2002. Since 2004 he is with Universidade de Brasilia, where he is now a Full Professor at the Computer Science Department. Dr. de Queiroz has published over 150 articles in Journals and conferences and contributed chapters to books as well. He also holds 46 issued patents. He is an elected member of the IEEE Signal Processing Society's Multimedia Signal Processing (MMSP) Technical Committee and a former member of other committees and editoral boards. He has been appointed an IEEE Signal Processing Society Distinguished Lecturer for the 2011-2012 term. He also organized many conferences and IEEE chapters. His research interests include image and video compression, multirate signal processing, and color imaging.
Speaker: Professor Zhong-Ping Jiang
Time: Tuesday December 4, 11:00am
Location: RH 214, Rogers Hall, Six MetroTech Center, Brooklyn
Measurement and verification (M&V) is the process of using measurements to reliably determine actual saving created within an individual facility by an energy management program. This talk will describe the basics of M&V, and introduce how M&V is conducted in the Republic of South Africa. Topics covered include the history of M&V in South Africa, the business structure, and the Eskom-led M&V protocols and guidelines of M&V. The talk will also present how the M&V profession is governed and regulated by the national professional body, the national stardard (the first in the world), and a national accreditation system of energy efficiency measurement and verification. Lastly, the talk will highlight the research and postgraduate student training in relation to M&V -- an fast evolving field where you find new research opportunities with applications of mathematics, control systems, power engineering and environmental psycology.
Xiaohua Xia is a professor in the Electrical, Electronic and Computer Engineering at the University of Pretoria, South Africa, director of the Centre of New Energy Systems, and the director of the South African National Hub for the Postgraduate Programme in Energy Efficiency and Demand-side Management. He was academically affiliated with the University of Stuttgart, Germany, the Ecole Centrale de Nantes, France, and the National University of Singapore before joining the University of Pretoria in 1998. Prof. Xia is a fellow of the Institute for Electronic and Electrical Engineers (IEEE), a fellow of the South African Academy of Engineering (SAAE), and a member of the Academy of Science of South Africa (ASSAf). He has an A rating from the South African National Research Foundation (NRF). He served as the chair of the Technical Committee of Non-linear Systems of the International Federation of Automatic Control (IFAC). He has been an associate editor of Automatica, IEEE Transactions on Circuits and Systems II, IEEE Transactions on Automatic Control, and specialist editor (control) of the SAIEE Africa Research Journal. His research interests are control systems and automation, and more recently, the modeling and optimization of energy systems. Prof Xia is a registered professional engineering with the Engineering Council of South Africa. He is a measurement and verification professional certified by the Association of Energy Engineers, the founding director and one of the two technical signatories of Onga Energy Pty Ltd – the first energy efficiency inspection body accredited by the South African National Accreditation Systems, and leads the measurement and verification team of the University of Pretoria.
Speaker: Doctor Christopher V. Hollot
Time: Thursday December 13, 11:00 am
Location: Brooklyn
Over the past decade, my research in the theory and application of feedback control has been aimed at biology engineering. Two projects I have been working on are in circadian rhythms and anemia management control. The technical part of this talk will primarily focus on the former topic, which will be interspersed with experiences in interdisciplinary research with biologists and medical clinicians.
C.V. Hollot received his Ph.D. in Electrical Engineering from the University of Rochester in 1984. He joined the Department of Electrical and Computer Engineering at the University of Massachusetts, Amherst in 1984, receiving the NSF PYI in 1988 and becoming a Fellow of the IEEE in 2004. His research interests are in the theory and application of feedback control.
Speaker: Professor Matthew M. Peet
Time: Tuesday December 18, 11:00 am
Location: Silleck Lounge, Jacob Building, Six MetroTech Center, Brooklyn
In this talk, we explore the possibilities and limits of using computation to analyze and control complex systems. The systems we consider are modeled by nonlinear, delayed or partial-differential equations. We begin the talk by proving that stability of a nonlinear vector field is decidable and deriving a bound on the complexity as a function of the rate of decay. This derivation explores concepts from convex optimization and converse Lyapunov theory. We then discuss extending these results to the difficult problems of stability and control of systems with delay or spatial dimension. Finally, we show how these computational techniques can be applied to knowledge discovery in immunology.
Matthew M. Peet received B.S. degrees in Physics and in Aerospace Engineering from the University of Texas at Austin in 1999 and the M.S. and Ph.D. in Aeronautics and Astronautics from Stanford University in 2001 and 2006, respectively. He was a Postdoctoral Fellow at the National Institute for Research in Computer Science and Control (INRIA) near Paris, France, from 2006-2008 where he worked in the SISYPHE and BANG groups. From 2008-2012 he was an Assistant Professor in the Mechanical, Materials, and Aerospace Engineering Department of the Illinois Institute of Technology. He is currently an Assistant Professor of Aerospace Engineering at Arizona State University (ASU) in the School for Engineering of Matter, Transport and Energy and director of the Cybernetic Systems and Controls Laboratory. A recent NSF CAREER awardee, his current research interests are in the role of computation as it is applied to the understanding and control of complex and large-scale systems. He has studied the use of optimization algorithms and Sum-of-Squares programming for the analysis of nonlinear systems and partial differential equations and has worked with applications in information networks and cancer therapy.