Colloquium Archive

September 5 Wednesday 1:30pm 369 Link Hall Professor Qing Zhao	Title:  Networking Cognitive Radios Speaker:  Professor Qing Zhao (University of California at Davis) Abstract: The "spectrum paradox" is by now widely recognized. On the one hand, the projected spectrum need for wireless devices and services continues to grow, and virtually all usable radio frequencies have already been allocated. On the other hand, extensive measurements conducted in recent years reveal that much of the prized spectrum lies unused at any given time and location. These measurements form the key rationale for secondary spectrum use through networked cognitive radios that are capable of sensing, learning, and exploiting spectrum opportunities while limiting interference to legacy systems.       In this talk, we discuss challenges and design issues that are unique to cognitive radio networks. Some of our recent work on spectrum sensing and cognition, spectrum opportunity tracking, and cognitive networking will be presented. About the Speaker:  Qing Zhao received the Ph.D. degree in Electrical Engineering in 2001 from Cornell University. From 2001 to 2003, she was a communication system engineer with Aware, Inc. in Massachusetts. She returned to academe in 2003 as a postdoctoral research associate at Cornell University. In 2004, she joined the ECE department at UC Davis where she is currently an assistant professor. Her research interests are in the general area of signal processing, communications, and wireless networking.       Qing Zhao received the 2000 IEEE Signal Processing Society Young Author Best Paper Award. She is an associate editor of IEEE Transactions on Signal Processing and an elected member of the Signal Processing for Communications committee of the IEEE Signal Processing Society. She is the PI of several NSF and DoD projects. http://www.ece.ucdavis.edu/~qzhao
September 19 Wednesday 1:30pm 369 Link Hall Prof. Sitharama Iyengar	Title: "Computational Framework for Content Based Image Retrieval" Speaker:  Prof. S. Sitharama Iyengar (Louisiana State University) Abstract: A fundamental aspect of content-based image retrieval (CBIR) is the extraction and the representation of a visual feature that is an effective discriminant between pairs of images. Among the many visual features that have been studied, the distribution of color pixels in an image is the most common visual feature studied. The standard representation of color for content-based indexing in image databases is the color histogram. Vector-based distance functions are used to compute the similarity between two images as the distance between points in the color histogram space. This talk presents an overall framework for CBIR and proposes an alternative real valued representation of color based on the nformation theoretic concept of entropy. A theoretical presentation of image entropy is accompanied by a practical description of the merits and limitations of image entropy compared to color histograms. Specifically, the L1 norm for color histograms is shown to provide an upper bound on the difference between image entropy values. Our initial results suggest that image entropy is a promising approach to image description and representation. Brief Bio: Prof. S.S.Iyengar is the Chairman and Roy Paul Daniels Chaired Professor of Computer Science at Louisiana State University, Baton Rouge, and is also the Satish Dhawan Chaired Professor at the Indian Institute of Science, Bangalore. His publications include 6 textbooks, 5 edited books and over 380 research papers. His research interests include high-performance algorithms, data structures, sensor fusion, data mining, and intelligent systems. He is a Fellow of IEEE, Fellow of ACM, Fellow of AAAS and Fellow of SDPS. He is a recipient of several IEEE awards, best paper awards, and the Distinguished Alumnus award of the Indian Institute of Science, Bangalore. He has served as the editor of several IEEE journals and is the founding editor-in-chief of the International Journal of Distributed Sensor Networks.
October 3 Wednesday 1:30pm 369 Link Hall Professor James Kurose	Title: Collaborative Adaptive Sensing of the Atmosphere: Challenges in End-to-End Sensor Networking Speaker:  Professor James Kurose - University of Massachusetts Abstract: The CASA project is an NSF Engineering Research Center investigating the design and implementation of a dense network of low-power meteorological radars whose goal is to collaboratively and adaptively sense the lowest few kilometers of the earth's atmosphere. In the first part of this talk we overview the CASA project, describe its computing and networking challenges, and overview the software/network architecture and implementation of the CASA testbeds. We also discuss the operation of CASA’s testbed during this spring’s tornado season in Oklahoma. In the second part of this talk, we focus on networking-related research issues and discuss our experiences in using user-specified preferences to drive the optimization of the network's radar scanning behavior. Throughout the talk, we’ll discussion of a number of interesting on-going and open research issues. Bio: Jim Kurose received a BA in Physics from Wesleyan University and a PhD in Computer Science from Columbia University. He is Distinguished University Professor (and past chairman) in the Department of Computer Science at the University of Massachusetts, where he is also Associate Director of the NSF Engineering Research Center for Collaborative Adaptive Sensing of the Atmosphere (CASA). Professor Kurose has been a Visiting Scientist at IBM Research, INRIA, Institute EURECOM, the University of Paris, LIP6, and Thomson Research Labs.       His research interests include network protocols and architecture, network measurement, sensor networks, multimedia communication, and modeling and performance evaluation. Dr. Kurose has served as Editor-in-Chief of the IEEE Transactions on Communications and was the founding Editor-in-Chief of the IEEE/ACM Transactions on Networking. He has served as Technical Program Co-Chair for IEEE Infocom, ACM SIGCOMM, ACM SIGMETRICS, and the ACM Internet Measurement Conference. He has received several conference best paper awards, as well as recognition for his teaching and educational activities, including the IEEE Taylor Booth Education Medal. With Keith Ross, he is the co-author of the textbook, "Computer Networking, a Top Down Approach (4th edition)," published by Addison-Wesley Longman. He is a Fellow of the IEEE and the ACM.
October 17 Wednesday 1:30pm 369 Link Hall Prof. Zhi-Quan (Tom) Luo	Title: Performance Analysis of Quasi-Maximum-Likelihood Detection Based on Semi-definite Relaxation Speaker:  Prof. Zhi-Quan (Tom) Luo - University of Minnesota Abstract: Consider the NP-hard problem of maximum likelihood (ML) detection for a multiple-input-multiple-output channel. We analyze two quasi-ML detectors based on semi-definite relaxation: the SDR detector for BPSK constellation and the PSK detector for M-PSK constellation. Both detectors are capable of delivering near-ML BER performance with a polynomial worst-case complexity. For a general class of random channels, we prove that the SDR detector provides a constant factor approximation in terms of the log-likelihood value, and this constant factor remains bounded with increasing system size. Furthermore, we show that the SNR gap between the ML and SDR detectors (expressed in dB) is bounded by a constant for large systems. For the PSK detector we show that each local maximum of the low-rank semi-definite relaxation that is feasible for the ML detection problem achieves at least a half of the maximum relative log-likelihood value, and for the BPSK case even yields an exact ML solution. Our analysis shows that the ML detection performance can be well approximated in polynomial time using semi-definite relaxation. Short 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 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 held a faculty position with the Department of Electrical and Computer Engineering, McMaster University, Canada, where he eventually served as the department head and held a Canada Research Chair in Information Processing. His research interests lie in the union of optimization algorithms, data communication and signal processing.          Dr. Luo serves on the IEEE Signal Processing Society Technical Committees on Signal Processing Theory and Methods (SPTM), and on the Signal Processing for Communications (SPCOM). He is a co-recipient of the 2004 IEEE Signal Processing Society's Best Paper Award, and has held editorial positions for several international journals including Journal of Optimization Theory and Applications, Mathematics of Computation, and IEEE Transactions on Signal Processing. He currently serves on the editorial boards for SIAM Journal on Optimization, Mathematical Programming, and Mathematics of Operations Research.
October 31 Wednesday 1:30pm 369 Link Hall Professor Michael Gastpar	Title: Structured Codes and the Capacity of Networks Speaker: Professor Michael Gastpar - Univ. of California, Berkeley Abstract:  To understand the fundamental performance limits in communication networks, two key ingredients are: code dependence and code structure. The former has been studied extensively in the context of the recent literature on cooperation. In this talk, we will discuss the latter. In the point-to-point communication problem, it is known that the performance of purely random codes (i.e., capacity) can sometimes be approached by structured codes (such as LDPC or lattice codes). Somewhat surprisingly, the situation is quite different in networks: There, structured codes are sometimes strictly better than purely random codes (thus, the latter cannot always attain capacity). We will discuss examples, novel coding theorems, and some capacity results. This is joint work with Bobak Nazer (UC Berkeley). Bio: Michael Gastpar (Ph.D. EPFL, 2002, M.S. UIUC, 1999, Dipl. El-Ing, ETH, 1997) has been an assistant professor at the University of California, Berkeley, since January 2003. He was also a student in electrical engineering and philosophy at the Universities of Edinburgh and Lausanne, and a summer researcher in the Mathematics of Communications Department at Bell Labs, Lucent Technologies. He won the 2002 EPFL Best Thesis Award and an NSF CAREER award in 2004.
November 14 Wednesday 1:30pm 369 Link Hall Professor Vivek Goyal	Title:  Benefiting from Disorder: Source Coding for Unordered Data Speaker:  Professor Vivek Goyal - MIT Abstract:  The order of symbols is not always relevant in a communication task. For example, the records in a database are often in arbitrary order, and in many inference problems the recipient will compute a permutation-invariant function of the source letters. This talk discusses the implications of order irrelevance on source coding, presenting results in several major branches of source coding theory: lossless coding, universal lossless coding, rate-distortion, high-rate quantization, and universal lossy coding.         The main conclusions demonstrate that there is a significant rate savings when order is irrelevant. In particular, lossless coding of n letters from a finite alphabet requires only O(log n) bits and universal lossless coding requires only n + o(n) bits for many countable alphabet sources. While this universally achievable rate is low, we also show that the redundancy cannot be made a negligible fraction of the coding rate under reasonable definitions of universality.        Results for lossy coding include distribution-free expressions for the rate savings from order irrelevance in various high-rate quantization schemes. Rate-distortion bounds are given, and it is shown that the analogue of the Shannon lower bound is loose at all finite rates. Joint work with Lav Varshney. See http://arxiv.org/abs/0708.2310 Bio:  Vivek Goyal joined the Department of Electrical Engineering and Computer Science of the Massachusetts Institute of Technology in 2004 and currently holds an Esther and Harold E. Edgerton chair. He previously worked in the Mathematics of Communications Research Department of Bell Laboratories, Lucent Technologies as a Member of Technical Staff and as Senior Research Engineer for Digital Fountain, Inc., Fremont, CA. His research interests include source coding theory, quantization theory, and practical, robust network content delivery.        Dr. Goyal is a Senior Member of IEEE and member of Phi Beta Kappa, Tau Beta Pi, Sigma Xi, Eta Kappa Nu, and SIAM. He received the 1998 Eliahu Jury Award of the University of California, Berkeley; the 2002 IEEE Signal Processing Society Magazine Award; and an NSF CAREER Award. He serves on IEEE Signal Processing Society's Image and Multiple Dimensional Signal Processing Technical Committee, on several technical program committees and as a permanent Co-Chair of the SPIE Wavelets conference series.
Cancelled November 28 Wednesday 1:30pm 369 Link Hall Professor Henry Kautz	Title:  Understanding Human Behavior from Low-Level Sensor Data Speaker:  Professor Henry Kautz - University of Rochester Abstract:   The convergence of advances in algorithms for probabilistic reasoning and the development of low-cost, easily-deployed sensors is reviving the dream of AI to develop systems that can understand the narrative of ordinary human life. On the reasoning side, the AI community is developing techniques that bridge the gap between propositional Bayesian representations and hierarchical models of goals, plans, and actions. On the sensing side, new technologies such as RFID tags, GPS, motes, and wearable multi-modal sensors allow us to gather direct information about various aspects of human experience. This talk will describe research on methods for learning probabilistic models of human performance of everyday high-level tasks, and applications to assistive technology and automated life diaries. About the speaker:   Henry Kautz is a Professor in the Department of Computer Science at the University of Rochester. He has been a Director at Kodak Research Laboratories, Professor at the University of Washington, and Department Head and scientist at AT&T Bell Laboratories. He is a Fellow of the AAAS, a Fellow of the AAAI, and winner of the Computers and Thought Award.
December 5  Wednesday 1:30pm 369 Link Hall Prof.Yao-Win (Peter) Hong	Title:  Cooperative Communications in Slotted ALOHA Random Access Networks Speaker:  Professor Yao-Win Peter Hong National Tsing Hua University, Taiwan Abstract: In this work, we analyze the stability region of the slotted ALOHA random access network with cooperative users. In a cooperative system, each user exploits spatial diversity by transmitting their packets through multiple relaying paths provided by their cooperative partners. Most works in the literature on cooperative communications focus on the physical layer aspects such as coding, modulation, transceiver signal processing etc. In this paper, we study the advantages of user cooperation from a MAC layer perspective and devise queuing strategies to exploit the cooperative diversity gains in a random access network. Specially, we propose two queuing strategies for the cooperative systems and study their respective stability regions as a measure of performance. We show that both schemes outperform the case with no cooperation. We then extend our system to networks that consist of multiple cooperating pairs and study the stability of the finite-user cooperative system. By treating each cooperative pair as a transmission entity, we derive inner bounds for the finite-user stability region and propose a ranking system to characterize the transmission entities' relative tendency of being stable (or unstable). About the speaker: Y.-W. Peter Hong received his B.S. degree in Electrical Engineering from National Taiwan University, Taipei, Taiwan, in 1999, and his Ph.D. degree in Electrical Engineering from Cornell University, Ithaca, NY, in 2005. In 2005, he joined the Institute of Communications Engineering/Department of Electrical Engineering in National Tsing Hua University, Hsinchu, Taiwan, where he is currently an Assistant Professor. His research is focused on cooperative communications, distributed signal processing for sensor networks, and PHY-MAC cross-layer designs for next generation wireless networks. He received the best paper award among unclassified papers in MILCOM 2005 and the best paper award for young authors from the IEEE IT/COM Society Taipei/Tainan chapter in 2005. ________________________________ Jointly Sponsored by Department of Electrical Engineering and Computer Science and CASE Center http://www.ecs.syr.edu/eecs_colloquium

Colloquium Archive