Seminars: Fall 2015


Date      Speaker From Title
Sep 15 Kamran Ayub NYU-Abu Dhabi Kamran's Talk
Sep 17 Thierry Blu Chinese University of Hong Kong Linear Expansion of Thresholds: a Tool for Approximating Image Processing Algorithms
Oct 2 Rudresh Ghosh University of Texas at Austin 2D Materials for Flexible Electronics
Oct 6 Bhaskar Krishnamachari University of Southern California Bandits and Newsvendors: Joint Online Learning and Optimization in Wireless Networks
Oct 8 Ruediger Urbanke EPFL How To Teach An Old Code A New Trick
Oct 14 Tsong-Lun Chu Brookhaven National Laboratory Development of a statistical testing approach for quantifying software reliability and its application to an example system
Oct 15 Yuval Kochman The Hebrew University of Jerusalem Information-theoretic secrecy over MIMO channels - schemes and new proofs
Oct 22 Naehyuck Chang Korea Advanced Institute of Science and Technology Design Automation of Things, the Future of EDA
Oct 29 Shivendra Panwar New York University Electrical and Computer Engineering at NYU Poly: Past , Present and Future
Nov 5 Anwar Walid Bell Labs Multipath TCP Congestion Control: from Theory to Implementation
Nov 13 Anna Choromanska New York University Optimization for large-scale machine learning: large data and large model
Nov 24 Young-Han Kim University of California, San Diego Point-to-point codes for interference channels: A journey toward high performance at low complexity
Dec 7 Anthony A. (Tony) Maciejewski Colorado State University Kinematically Redundant Robots: The Promise of Human-Like Dexterity
Dec 8 Diana Marculescu Carnegie Mellon University The Quest for Energy Aware Computing
Dec 10 Mohammad Ali Maddah-Ali Bell Labs Coded MapReduce
Dec 14 Aditya Ramamoorthy Iowa State University Combinatorial Designs for distributed data storage and distributed function computation


Kamran's Talk

Speaker:Kamran Ayub, NYU-Abu Dhabi
Time: 11:00 am - 12:00 pm, Sep 15, 2015
Location: 2MTC, 10th floor, Room 10.099, Brooklyn, NY

This talk will discuss two major concerns in a wireless sensor network’s security: Inter-network security,and Intra-Network security of WSN. I propose a new framework for the data integrity and security of WSN communication.

Encrypsion and other complex algorithm based security solutions need high processing power that’s not adaptable for the wireless sensor networks. In my proposed solution, Clustering based adaption features are used with the Radio Frequency Identification “RFID” (under Impulse Radio UWB). Each Sink node has an active RFID module which works at 2.4 GHz and uses a separate channel for the source identification. Hence secures inter-network communication.

Modern Wireless Sensor Networks need to be connected with variety of other conventional networks, Ethernet is common example. In such hybrid network infrastructure, most serious attacks are placed at “Intra-Network communication point”, that is at/around the Gateway. I proposed to use a layer 3 gateway with IPS (Intrusion Prevention System) on Ethernet side and IDS (Intrusion Detection System) on Wireless Sensor Network side.

This will provide a secure tunnel between both networks for data communication.

About the Speaker: Kamran Ayub received, M. Eng. (Telecommunications and Networks) Degree from London South Bank University London UK in 2008 and B. Eng. and Ph.D. from Riga Technical University, Riga Latvia in 2005 and 2015 respectively. He has successfully defended his Ph.D. (Wireless Sensor Networks) in June 2015. He has over 10 years of Industrial experience in the field of Telecoms and Network Security.

Currently he is working in Technology Group NYU-Abu Dhabi. Before NYU he worked with UAE Govt. on multiple projects including Ministry of Defense, MASDAR Smart City. He has also worked with BT (British Telecoms) Labs (Ipswich –UK) and Royal Airforce College.

Since 2008, he has been with Technology Group New York University. His research focuses Ultra-Wideband Communication Systems, Ad-hoc and Sensor Networks, Body area networks, and Wireless Security. He is the author of many research papers. He was awarded the best presentation award in ICNGCCT-2015 Dubai.

Linear Expansion of Thresholds: a Tool for Approximating Image Processing Algorithms

Speaker:Thierry Blu, the Chinese University of Hong Kong, Department of Electronic Engineering
Time: 11:00 am - 12:00 pm, Sep 17, 2015
Location: LC433, 5 MetroTech Center, Brooklyn, NY

Contrary to the usual processing approaches which consist in approximating all the pixels of an image (often by optimizing some criterion), we propose to approximate the processing itself using a linear combination of a few basic non-linear processings --- "thresholds". Accordingly, we term this approach "Linear Expansion of Thresholds" (LET). The whole adaptivity of LET algorithms is then concealed in the few (linear) coefficients of the representation, which can be optimized using the same criterion as the one chosen in usual approaches (e.g., MAP, sparse regularization, total variation, etc.) or new statistical criteria like Stein's Unbiased Risk Estimate (SURE). This approach lends itself quite well to iterations (i-LET) allowing to refine first-order solutions.

The main advantage of the LET representation is its high implementation efficiency due to a large dimensionality reduction (from the many pixels of an image, to the few coefficients of the LET representation), and due to its linearity, which preserves the convexity and quadraticity of the optimization criterion. This approach has been applied with success to several image distortion problems: image denoising/deconvolution (SURE-based criterion), and sparse image restoration (data-term + l1 regularization). In all these applications, the quality of the results either reach, or set a new state-of-the-art, while being substantially faster.

About the Speaker: Thierry Blu was born in Orléans, France, in 1964. He received the "Diplôme d'ingénieur" from École Polytechnique, France, in 1986 and from Télécom Paris (ENST), France, in 1988. In 1996, he obtained a Ph.D in electrical engineering from ENST for a study on iterated rational filterbanks, applied to wideband audio coding.

Between 1998 and 2007, he was with the Biomedical Imaging Group at the Swiss Federal Institute of Technology (EPFL) in Lausanne, Switzerland. He is now a Professor in the Department of Electronic Engineering, The Chinese University of Hong Kong. Dr. Blu was the recipient of two best paper awards from the IEEE Signal Processing Society (2003 and 2006). He is also coauthor of a paper that received a Young Author best paper award (2009) from the same society. He has been an Associate Editor for the IEEE Transactions on Image Processing (2002-2006), the IEEE Transactions on Signal Processing (2006-2010), Elsevier Signal Processing (2008-2011). He was a member of the IEEE Signal Processing Theory and Methods Technical Committee (2008-2013). He is currently on the board of Eurasip J. on Image and Video Processing (since 2010).

He was elected Fellow of the IEEE in 2012 for "fundamental contributions to approximation theory in signal and image processing".

2D Materials for Flexible Electronics

Speaker:Rudresh Ghosh, University of Texas at Austin
Time: 11:00 am - 12:00 pm, Oct 2, 2015
Location: LC433, 5 MetroTech Center, Brooklyn, NY

The extra-ordinary properties of graphene have generated immense interest in the research community. However, the lack of a band-gap makes graphene based digital electronics a difficult challenge. In order to get around this engineers and scientists are exploring other two dimensional (2D) materials. Layered transition metal dichalcogenides (TMDs) which can be metallic, insulating as well semi-conductors are being explored as possible complements of silicon in beyond Moore’s law electronics. Possible applications of these materials include low power, high performance electronics, flexible electronics, novel opto-electronic devices and chemical sensors. Despite initial results showing great promise, lab to consumer electronics transition has been slow. This can be partially blamed on the lack of mature synthesis routes that can provide high yield, high quality material. In this talk we present a brief overview of our efforts in the material synthesis of TMDs and how electronic devices based on these synthesized materials compare to those obtained from exfoliated samples. We also present novel characterization techniques that have been tailored to suit the needs of these new materials. We wrap up the talk with a brief overview of where we envision this field to be headed.

About the Speaker: Dr. Rudresh Ghosh received his Bachelor's of Science degree from the University of Calcutta (2004) and his Masters of Science from the Indian Institute of Technology, Bombay (2006), both in Physics. For his PhD, he worked with Dr. Rene Lopez at the University of North Carolina at Chapel Hill (UNC). As part of the Energy Frontier Research Center at UNC his work focused on using pulsed laser deposition for tailoring thin film growth for sensors and photo-voltaic applications. After obtaining his PhD (2012) he moved to the University of Texas at Austin where he currently works as a post-doctoral fellow at the Microelectronics Research Center. His current research focuses on large area growth and characterization of 2-Dimensional materials.

Bandits and Newsvendors: Joint Online Learning and Optimization in Wireless Networks

Speaker:Bhaskar Krishnamachari, University of Southern California
Time: 11:00 am - 12:00 pm, Oct 6, 2015
Location: 2MTC, 9th floor, Room 9.101, Brooklyn, NY

Algorithms for online learning and decision-making under uncertainty have become popular in recent years to improve the performance of wireless networks in unknown dynamic environments. I will give a brief overview of certain classic problem formulations such as multi-armed bandits (MAB) and news-vendor problems, talk about their applications to wireless networking, and present some recent results from my group's research in this area. These include results for decentralized MAB, combinatorial MAB, contextual MAB, multi-period newsvendors, and optimized robotic network formation in unknown environments. This talk will cover joint work with USC students Dr. Yi Gai, Pranav Sarkar, Parisa Mansourifard, and Shangxing Wang, and faculty collaborators Rahul Jain (USC), Tara Javidi (UCSD), and Nora Ayanian (USC).

About the Speaker: Bhaskar Krishnamachari is an Associate Professor and Ming Hsieh Faculty Fellow in Electrical Engineering, and Director of the Autonomous Networks Research Group ( at the University of Southern California's Viterbi School of Engineering. He works on the design and analysis of algorithms and protocols for next generation wireless networks. His co-authored papers have received best paper awards at IPSN (2004, 2010), MSWiM (2006) and MobiCom (2010), a best paper runner-up at SECON (2012), and a top-three paper at MSWiM (2014). He has received the NSF CAREER award (2004), the ASEE Terman Award (2010), and has been included on Technology Review Magazine's TR-35 list (2011), and Popular Science's Brilliant 10 list (2015). He has authored a book titled "Networking Wireless Sensors" published by Cambridge University Press. He is an Editor for the ACM Transactions on Sensor Networks, was the TPC Co-Chair for IPSN 2015, and is a TPC Co-Chair for WiOpt 2016.

How To Teach An Old Code A New Trick

(Jack Keil Wolf Lecture)

Speaker:Ruediger Urbanke, EPFL
Time: 11:00 am - 12:00 pm, Oct 8, 2015
Location: LC400, 5 MetroTech Center, Brooklyn, NY

Our digital lifes depend heavily on our ability to efficiently and reliable transmit information over long distances. It is therefore not surprising that much effort has been dedicated to devising clever schemes to accomplish this. I will go back in time to Reed-Mueller codes, one of the pioneering codes discovered in the mid fifties and I will ask the question: "What do you get when you combine these classical algebraic codes, EXIT functions from iterative coding, and the fact that monotone symmetric Boolean functions have sharp thresholds?”

[Based on joint work with S. Kudekar, S. Kumar, M. Mondelli, H. D. Pfister, and E. Sasoglu]

About the Speaker: R. Urbanke has been obsessed with questions in coding theory for the past 20 years. Fortunately his progress has been slow so that there are many problems left for him for the next 20 years. He enjoys sabbaticals and dreams to run the NYC marathon some day but does not like to practice. For more information, see

Development of a statistical testing approach for quantifying software reliability and its application to an example system

Speaker:Tsong-Lun Chu, Brookhaven National Laboratory
Time: 11:00 am - 12:00 pm, Oct 14, 2015
Location: 2MTC, 10th floor, Room 10.099, Brooklyn, NY

Brookhaven National Laboratory (BNL) developed an approach for performing statistical testing of a digital protection system in terms of the contexts defined in a Probabilistic Risk Assessment (PRA). The approach includes (1) use of PRA in defining the contexts for testing, (2) development of operational profiles for sampling test cases, (3) use of a RELAP model in simulating the test cases and generating the input signals to the protection system to be tested, (4) establishment of a test configuration for supplying the inputs to the protection system and retrieving the results, and (5) analysis of the results and quantification of software failure probability. In addition, PRA information can be used in determining the importance of the protection system and estimating an acceptable software failure probability.

About the Speaker: Dr. Tsong-Lun Chu received his PHD in Nuclear Engineering from UCLA in 1983. He has been working at Brookhaven National Laboratory since 1984 in the area of Probabilistic Risk Assessment (PRA) of nuclear power plants. He performed research on PRA methods, and develop risk assessment models for addressing regulatory issues in support of the US Nuclear Regulatory Commission. In 1999, he started working on digital system reliability, that is, development of methods for quantifying hardware and software reliability of digital instrumentation and control systems at nuclear power plants.

Information-theoretic secrecy over MIMO channels - schemes and new proofs

Speaker:Yuval Kochman, Hebrew University of Jerusalem
Time: 11:00 am - 12:00 pm, Oct 15, 2015
Location: 2MTC, 10th floor, Room 10.099, Brooklyn, NY

We revisit the problems of MIMO wiretap and confidential broadcast. Our goal is twofold: first, to re-derive capacity results in a concise and clear manner, and second, to provide modular capacity-approaching communication schemes. First we consider the MIMO wiretap channel under a covariance constraint. The secrecy capacity was established by Liu and Shamai, and the associated optimal input covariance matrix was proven by Bustin et al. By using linear algebra (GSVD) analysis only, without any information-theoretic considerations, we re-derive the optimal covariance matrix. We also explain how our proof can be translated into an explicit layered coding scheme with SISO secrecy codes and successive interference cancellation or dirty-paper coding within each layer. Such a scheme enjoys the same advantages that SVD or V-BLAST schemes have in MIMO problems without secrecy constraints. Next we consider the confidential broadcast problem under a covariance constraint, earlier studied by Liu et al. The capacity region was shown to be rectangular and achieved using dirty paper coding for both the receivers. We re-derive the capacity region (and the associated input covariance matrix) using a GSVD-based analysis, and propose a layered coding scheme with SISO codes.

Joint work with Anatoli Khina (CalTech) and Ashish Khisti (Toronto)

About the Speaker: Yuval Kochman received the B.Sc. (cum laude), M.Sc. (cum laude), and Ph.D. degrees from Tel Aviv University in 1993, 2003, and 2010, respectively, all in electrical engineering. During 2009–2011, he was a with the Signals, Information and Algorithms Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA. Since 2012, he has been with the School of Computer Science and Engineering, Hebrew University of Jerusalem. Outside academia, he has worked in the areas of radar and digital communications. His research interests include information theory, communications and signal processing.

Design Automation of Things, the Future of EDA

Speaker:Naehyuck Chang, Korea Advanced Institute of Science and Technology
Time: 11:00 am - 12:00 pm, Oct 22, 2015
Location: 2MTC, 10th floor, Room 10.099, Brooklyn, NY

This talk introduces a new area of Design Automation, Design Automation of Things, that attempts to apply Electronics Design Automation design, optimization and synthesis methods to other applications (Things.) In this talk, we introduce the first step toward systematic electric vehicle (EV) design-time and runtime optimization. We develop instantaneous power consumption modeling of an EV by the curb weights, speed, acceleration, road slope, passenger and cargo weights, motor capacity, and so on, as a battery discharge model. To insure model fidelity, we fabricate a lightweight custom EV, perform extensive measurement, and derive model coefficients using multivariable regression analysis. We estimate the EV instantaneous power consumption of a given speed and route profiles and verify the estimation fidelity with a real test run data. This talk will introduce several research challenges and opportunities based on the EV model for accurate range estimation and minimum-energy EV design/operation.

About the Speaker: Naehyuck Chang is a Full Professor at the Department of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST) from 2014. Before he joined KAIST, he was with the Department of Computer Science and Engineering, Seoul National University from 1997 to 2014. Dr. Chang also served as a Vice Dean of College of Engineering, Seoul National University from 2011 to 2013. His current research interests include low-power embedded systems and Design Automation of Things such as systematic design and optimization of energy storage systems and electric vehicles.

Dr. Chang is the Past Chair of ACM SIGDA (Special Interest Group on Design Automation), a Fellow of IEEE and an ACM Distinguished Scientist. Dr. Chang is the Editor-in-Chief of the ACM (Association for Computing Machinery) Transactions on Design Automation of Electronics Systems, and an Associate Editor of IEEE Transactions on Very Large Scale Integration Systems. He also served for IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, IEEE Embedded Systems Letters, ACM Transactions on Embedded Computing Systems, and so on, as an Associate Editor.

Dr. Chang is (was) the General Co-Chair of VLSI-SoC (Very Large Scale Integration) 2015, ICCD (International Conference on Computer Design) 2014 and 2015, ISLPED (International Symposium on Low-Power Electronics and Design) 2011, etc.

Dr. Chang is the Technical Program Chair of DAC (Design Automation Conference) 2016. He was the Technical Program (Co-)Chair of ASP-DAC (Asia and South Pacific Design Automation Conference) 2015, ICCD 2014, CODES+ISSS (Hardware Software Codesign and System Synthesis) 2012, ISLPED 2009, etc.

Dr. Chang is the winner of the 2014 ISLPED Best Paper Award, 2011 SAE Vincent Bendix Automotive Electronics Engineering Award, 2011 Sinyang Academic Award, 2009 IEEE SSCS International SoC Design Conference Seoul Chapter Award, and several ISLPED Low-Power Design Contest Awards in 2002, 2003, 2004, 2007, 2012, and 2014.

Electrical and Computer Engineering at NYU Poly: Past , Present and Future

Speaker:Shivendra Panwar, New York University
Time: 11:00 am - 12:00 pm, Oct 29, 2015
Location: 2MTC, 10th floor, Room 10.099, Brooklyn, NY

If one word can be used to describe “Brooklyn Poly”, past, present and I believe in the future, it is the word “scrappy”, perhaps a good word to describe all things Brooklyn! This certainly holds true for our department, which has been in existence since 1885. I will start by giving some glimpses into its history, before moving to where we are today. This will includes facts and figures, research highlights, the student body and faculty. I will then point out the challenges we face as a department today, and the direction of the department of electrical and computer engineering in the future, including where we fit in NYU’s emerging plans.

About the Speaker: Shivendra S. Panwar is a Professor and Dept. Head of the Electrical and Computer Engineering Department at New York University Tandon School of Engineering. He received the B.Tech. degree in electrical engineering from the Indian Institute of Technology Kanpur, in 1981, and the M.S. and Ph.D. degrees in electrical and computer engineering from the University of Massachusetts, Amherst, in 1983 and 1986, respectively. He is currently the Director of the New York State Center for Advanced Technology in Telecommunications (CATT), and the Faculty Director of the NY City Media Lab. He spent the summer of 1987 as a Visiting Scientist at the IBM T.J. Watson Research Center, Yorktown Heights, NY, and has been a Consultant to AT&T Bell Laboratories, Holmdel, NJ. His research interests include the performance analysis and design of networks. Current work includes cooperative wireless networks, switch performance and multimedia transport over networks. He has served as the Secretary of the Technical Affairs Council of the IEEE Communications Society. He is a co-editor of two books, Network Management and Control, Vol. II, and Multimedia Communications and Video Coding, both published by Plenum. He has also co-authored TCP/IP Essentials: A Lab based Approach, published by the Cambridge University Press. He was awarded, along with Shiwen Mao, Shunan Lin and Yao Wang, the IEEE Communication Society's Leonard G. Abraham Prize in the Field of Communication Systems for 2004. He won, along with Zhengye Liu, Yanming Shen, Keith Ross, and Yao Wang, the IEEE Multimedia Communications Best Paper Award for 2011. He is an IEEE Fellow.

Multipath TCP Congestion Control: from Theory to Implementation

Speaker:Anwar Walid, Bell Labs
Time: 11:00 am - 12:00 pm, Nov 5, 2015
Location: 2MTC, 10th floor, Room 10.099, Brooklyn, NY

Multipath TCP (MPTCP), an experimental IETF standard, has the potential to significantly improve application performance by transparently taking advantage of the increasingly available multiple network paths and multiple interfaces on user devices. In this talk we describe our recent research on MPTCP congestion control, which spans control theory and open-source implementation. We describe our “Balia” congestion control algorithm, a key feature of the new open-source v0.90 release of MPTCP Linux Kernel implementation, and review the theory behind its design that enables it to optimize performance tradeoffs. We highlight applications in wireless 5G, data centers and SDN-enabled networks. Ongoing research directions will also be discussed.

About the Speaker: Anwar Walid is a Distinguished Member of Technical Staff with the Mathematics of Networks and Systems Research Department in Bell Labs (Murray Hill, N.J.). He also served as Director of Research Partnership and University Collaborations, Bell Labs Chief Scientist Office. He received the B.S. degree in Electrical and Computer Engineering from Polytechnic of New York University, and the Ph.D. in Electrical Engineering from Columbia University, New York. He has 11 patents granted and more than 10 pending on various aspects of networking and computing. He received Best Paper Award from ACM SIGMETRICS, IFIP Performance, and the IEEE LANMAN. He contributed to the Internet Engineering Task Force (IETF) and co-authored RFCs. He is an associate editor of IEEE/ACM Transactions on Cloud Computing and IEEE Network Magazine, and was associate editor of the IEEE/ACM Transactions on Networking (2009-2014). He served as Technical Program Co-chair of IEEE INFOCOM 2012. Since 2009, he has been an adjunct Professor at Columbia University Electrical Engineering department. Dr. Walid is an IEEE Fellow and an elected member of the IFIP Working Group 7.3.

Optimization for large-scale machine learning: large data and large model

Speaker:Anna Choromanska, New York University
Time: 1:00 pm - 2:00 pm, Nov 13, 2015
Location: 2MTC, 9th floor, Room 9.101, Brooklyn, NY

The talk will focus on selected challenges in modern large-scale machine learning in two settings: i) large data setting and ii) large model (deep learning) setting. The first part of the talk will focus on the case when the learning algorithm needs to be scaled to large data. The multi-class classification problem will be addressed, where the number of classes (k) is extremely large, with the goal of obtaining train and test time complexity logarithmic in the number of classes. A reduction of this problem to a set of binary classification problems organized in a tree structure will be discussed. A top-down online tree construction approach for constructing logarithmic depth trees will be demonstrated, which is based on a new objective function. Under favorable conditions, the new approach leads to logarithmic depth trees that have leaves with low label entropy. Discussed approach comes with theoretical guarantees following from convex analysis, though the underlying problem is inherently non-convex. The second part of the talk focuses on the theoretical analysis of more challenging non-convex learning setting, deep learning with multilayer networks. Despite the success of convex methods, deep learning methods, where the objective is inherently highly non-convex, have enjoyed a resurgence of interest in the last few years and they achieve state-of-the-art performance. In the second part of the talk we move to the world of non-convex optimization where recent findings suggest that we might eventually be able to describe these approaches theoretically. The connection between the highly non-convex loss function of a simple model of the fully-connected feed-forward neural network and the Hamiltonian of the spherical spin-glass model will be established. It will be shown that under certain assumptions i) for large-size networks, most local minima are equivalent and yield similar performance on a test set, (ii) the probability of finding a “bad” local minimum, i.e. with high value of loss, is non-zero for small-size networks and decreases quickly with network size, (iii) struggling to find the global minimum on the training set (as opposed to one of the many good local ones) is not useful in practice and may lead to overfitting. Discussion of open problems concludes the talk.

About the Speaker: Anna Choromanska is a Post-Doctoral Associate in the Computer Science Department at Courant Institute of Mathematical Sciences, New York University. She is working in the Computational and Biological Learning Lab, which is a part of Computational Intelligence, Learning, Vision, and Robotics Lab, of prof. Yann LeCun. She graduated with her PhD from Columbia University, Department of Electrical Engineering, where she was the The Fu Foundation School of Engineering and Applied Science Presidential Fellowship holder. She was advised by prof. Tony Jebara. She completed her MSc with distinctions in the Department of Electronics and Information Technology, Warsaw University of Technology with double specialization, Electronics and Computer Engineering and Electronics and Informatics in Medicine. She was working with various industrial institutions, including AT&T Research Laboratories, IBM T.J. Watson Research Center and Microsoft Research New York. Her research interests are in machine learning, optimization and statistics with applications in biomedicine and neurobiology. She also holds a music degree from Mieczyslaw Karlowicz Music School in Warsaw, Department of Piano Play. She is an avid salsa dancer performing with the Ache Performance Group. Her other hobbies is painting and photography.

Point-to-point codes for interference channels: A journey toward high performance at low complexity

Speaker:Young-Han Kim, University of California, San Diego
Time: 11:00 am - 12:00 pm, Nov 24, 2015
Location: 2MTC, 9th floor, Room 9.101, Brooklyn, NY

For high data rates and massive connectivity, the next-generation cellular networks are expected to deploy many small base stations. While such dense deployment provides the benefit of bringing radio closer to end users, it also increases the amount of interference from neighboring cells. Consequently, smart management of interference would become one of the key enabling technologies for high-spectral-efficiency, low-power, broad-coverage wireless communication.

In this talk, we discuss recent developments in channel coding techniques for interference channels, primarily focusing on the sliding-window superposition coding scheme. This coding scheme achieves the performance of simultaneous decoding with point-to-point channel codes and low-complexity decoding. Simulation results demonstrate that sliding-window superposition coding can sometimes double the performance of the conventional method of treating interference as noise, still using the standard LTE turbo codes.

Joint work with Seok-Ki Ahn, Bernd Bandemer, Chiao-Yi Chen, Abbas El Gamal, Kwang Taik Kim, Hosung Park, Eren Sasoglu, and Lele Wang.

About the Speaker: Young-Han Kim received his B.S. degree in Electrical Engineering from Seoul National University in 1996 and his Ph.D. degree in Electrical Engineering (M.S. degrees in Statistics and in Electrical Engineering) from Stanford University in 2006. Since then he has been a faculty member in the Department of Electrical and Computer Engineering at the University of California, San Diego, where he is currently an Associate Professor.

Professor Kim is a recipient of the NSF CAREER Award (2008), the US-Israel BSF Bergmann Memorial Award (2009), the IEEE Information Theory Paper Award (2012), and the first IEEE James L. Massey Research and Teaching Award (2015). He is an IEEE Fellow. His research interests include information theory, communication engineering, and data science.

Kinematically Redundant Robots: The Promise of Human-Like Dexterity

Speaker:Anthony A. (Tony) Maciejewski, Colorado State University
Time: 2:00 pm - 3:00 pm, Dec 7, 2015
Location: 2MTC, 10th floor, Room 10.099, Brooklyn, NY

The vast majority of robots in use today operate in very structured environments, e.g., in factory assembly lines, and possess only those limited motion capabilities required to perform specific tasks. While these robots can outperform humans in terms of speed, strength, and accuracy for these tasks, they are no match for the dexterity of human motion. Part of a human's inherent advantage over industrial robots is due to the large number of degrees of freedom in the human body. Articulated, i.e., jointed, motion systems that possess more degrees of freedom than the minimum required to perform a specified task are referred to as kinematically redundant. In an effort to mimic the dexterity of biological systems, researchers have built a number of kinematically redundant robotic systems, e.g., anthropomorphic arms, multi-fingered hands, dual-arm manipulators, and walking machines. While these systems vary in their appearance and intended applications, they all require motion control strategies that coordinate large numbers of joints to achieve the high degree of dexterity possible with redundant systems. This talk will discuss the issues that arise when designing such strategies, frequently drawing on the use of the singular value decomposition, including the characterization of redundancy, the quantification of dexterity, and the development of efficient and numerically stable motion control algorithms that simultaneously optimize multiple criteria.

About the Speaker: Anthony A. (Tony) Maciejewski received the B.S., M.S., and Ph.D. degrees in Electrical Engineering in 1982, 1984, and 1987, respectively, all from The Ohio State University. From 1988 to 2001, he was a Professor of Electrical and Computer Engineering at Purdue University. In 2001, he joined Colorado State University where he is currently the Head of the Department of Electrical and Computer Engineering. He has co-authored over 250 technical publications in the areas of robotics and high-performance computing and served on eight journal editorial boards and over 100 conference program committees. He is a Fellow of IEEE and currently serves as the Vice-President of Financial Activities for the Robotics and Automation Society. A complete up-to-date vita is available at

The Quest for Energy Aware Computing

Speaker:Diana Marculescu, Carnegie Mellon University
Time: 2:00 pm - 3:00 pm, Dec 8, 2015
Location: 2MTC, 9th floor, Room 9.101, Brooklyn, NY

How do natural systems endure and how is nature inherently renewable? Can we learn from the supreme engineer - nature - how to design systems that are either energy aware by themselves or aid in achieving true sustainability in man-made systems? Electronic system design has benefited from decades of reliable and predictable functionality, but this trend is likely to slow down in future technology nodes. To support a path toward energy aware computing, a holistic approach toward addressing energy awareness, reliability, and variability at all the levels in the system is required. Furthermore, while design tools and methodologies for individual systems is relatively mature, achieving true energy efficiency for many real-life applications is still emerging. This talk will discuss our work on achieving superior performance and power efficiency for silicon systems in the presence of challenges induced by manufacturing process uncertainties and will unravel applications of classic tool sets to the design and analysis of large scale real-life applications.

About the Speaker: Diana Marculescu is a Professor of Electrical and Computer Engineering at Carnegie Mellon University. She received the Dipl.Ing. degree in computer science from the Polytechnic University of Bucharest, Bucharest, Romania, and the Ph.D. degree in computer engineering from the University of Southern California, Los Angeles, CA, in 1991 and 1998, respectively. Her current research interests include energy- and reliability-aware computing, and CAD for non-silicon applications, including e-textiles, computational biology, and sustainability. Diana was a recipient of the National Science Foundation Faculty Career Award from 2000 to 2004, the ACM SIGDA Technical Leadership Award in 2003, the Carnegie Institute of Technology George Tallman Ladd Research Award in 2004, and the Best Paper Award at the IEEE Asia and South Pacific Design Automation Conference in 2005, the Best Paper Award at the IEEE International Conference on Computer Design in 2008, the Best Paper Award at the International Symposium on Quality Electronic Design in 2009, and the Best Paper Award at the IEEE Trans. on Very Large Scale Integrated (VLSI) Systems in 2011. She was an IEEE Circuits and Systems Society Distinguished Lecturer from 2004 to 2005 and the Chair of the Association for Computing Machinery (ACM) Special Interest Group on Design Automation from 2005 to 2009. Diana was the Technical Program Chair of the ACM/IEEE International Workshop on Logic and Synthesis in 2004, the ACM/IEEE International Symposium on Low Power Electronics and Design in 2006, and the General Chair of the same symposia in 2003 and 2007, respectively. She also served as the Technical Program Chair of the IEEE/ACM International Symposium on Networks-on-Chip in 2012, the IEEE/ACM International Conference on Computer-Aided Design in 2013, and was the General Chair for the same conferences in 2015. Diana is currently an Associate Editor for IEEE Transactions on Computers and has served in the same position for the IEEE Transactions on VLSI Systems and the ACM Transactions on Design Automation of Electronic Systems. She was selected as an ELATE Fellow (2013-2014), and is the recipient of an Australian Research Council Future Fellowship (2013-2017) and the Marie R. Pistilli Women in EDA Achievement Award (2014). Diana is an IEEE Fellow and an ACM Distinguished Scientist.

Coded MapReduce

Speaker:Mohammad Ali Maddah-Ali, Bell Labs, Alcatel-Lucent
Time: 11:00 am - 12:00 pm, Dec 10, 2015
Location: 2MTC, 10th floor, Room 10.099, Brooklyn, NY

MapReduce is a commonly used framework for executing data-intensive tasks on distributed server clusters. We present ''Coded MapReduce", a new framework that enables and exploits a particular form of coding to significantly reduce the inter-server communication load of MapReduce. In particular, Coded MapReduce exploits the repetitive mapping of data blocks at different servers to create coded multicasting opportunities in the shuffling phase, cutting down the total communication load by a multiplicative factor that grows linearly with the number of servers in the cluster. We will further discuss the tradeoff between the ''computation load'' and the ''communication load" in distributed computing.

About the Speaker: Mohammad Ali Maddah-Ali received the B.Sc. degree from Isfahan University of Technology, Isfahan, Iran, and the M.A.Sc. degree from the University of Tehran, Tehran, Iran, both in electrical engineering. From 2002 to 2007, he was with the Coding and Signal Transmission Laboratory (CST Lab), Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada, working toward the Ph.D. degree. From 2007 to 2008, he worked at the Wireless Technology Laboratories, Nortel Networks, Ottawa, ON, Canada. From 2008 to 2010, he was a post-doctoral fellow at the Department of Electrical Engineering and Computer Sciences in the University of California at Berkeley. Since September 2010, he has been at Bell Laboratories, Alcatel-Lucent, Holmdel, NJ, as a communication network research scientist. His research interests include wireless communications, content delivery networks, and multiuser information theory. Dr. Maddah-Ali received several awards including NSERC Postdoctoral Fellowship in 2007, the best paper award at IEEE International Conference on Communications (ICC) in 2014, and the IEEE Communications Society and Information Theory Society joint paper award in 2015.

Combinatorial Designs for distributed data storage and distributed function computation

Speaker:Aditya Ramamoorthy, Iowa State University
Time: 1:30 pm - 2:30 pm, Dec 14, 2015
Location: 2MTC, 9th floor, Room 9.101, Brooklyn, NY

Combinatorial design theory has its roots in recreational mathematics and is concerned with the arrangement of the elements of a finite set into subsets, such that the collection of subsets has certain “nice” properties. Interpreting designs in the right manner can often yield interesting links and conclusions in various areas within communications.

In the first part of the talk, I will discuss our work on constructing regenerating codes from combinatorial designs. Regenerating codes have been proposed as an efficient mechanism for dealing with the problem of reliability in large scale distributed storage systems. These systems also have additional requirements pertaining to repair. When nodes fail, the system needs to be repaired in a speedy manner, by consuming as few resources (drives accessed, energy etc.) as possible. We will demonstrate that combinatorial designs are a natural fit for this problem and outline our constructions.

Following this, I will overview our work that relates combinatorial designs with network coding based function computation. I will demonstrate that an appropriate interpretation of designs can construct a family of directed acyclic networks that have several interesting properties. In particular, our work shows that the computation rate of such networks depends significantly on the source alphabets. This is in stark contrast with multiple unicast networks where the rate is independent of the source alphabet.

The talk will be self-contained; no background in combinatorial designs and/or network coding will be assumed.

About the Speaker: Aditya Ramamoorthy is an Associate Professor of Electrical and Computer Engineering at Iowa State University. He received his B. Tech. degree in Electrical Engineering from the Indian Institute of Technology, Delhi in 1999 and the M.S. and Ph.D. degrees from the University of California, Los Angeles (UCLA) in 2002 and 2005 respectively. From 2005 to 2006 he was with the data storage signal processing group at Marvell Semiconductor Inc. His research interests are in the areas of network information theory, channel coding and signal processing for nanotechnology and bioinformatics. Dr. Ramamoorthy served as an associate editor for the IEEE Transactions on Communications from 2011 -- 2014. He is the recipient of the 2012 Iowa State University's Early Career Engineering Faculty Research Award, the 2012 NSF CAREER award, and the Harpole-Pentair professorship in 2009 and 2010.