ESE Seminars & Events

ESE Special Seminar Series: Spring 2013

Seminars will be held in Towne 337 at 11:00 AM unless otherwise specified.

Ozan Candogan January 22
Ozan Candogan, Massachusetts Institute of Technology
Read the Abstract and Bio

Abstract: Multi-item iterative auctions are a class of mechanisms that are commonly employed in practice, for instance, in the context of spectrum and procurement auctions. However, the existing iterative auction formats that are provably efficient have certain limitations. Specifically, they are either restricted to environments that do not allow for value complementarity between different items, or they require complex pricing structures. In this work, we develop new practical and efficient iterative auctions for multi-item settings that exhibit both value complementarity and substitutability.  We obtain such auctions by focusing on a natural class of valuation functions that admit a compact representation, which we refer to as graphical valuations. For special classes of graphical valuations, such as tree valuations, our auctions implement the efficient outcome using item pricing, i.e., offering an anonymous price for each item. However, we establish that this simple pricing structure is not sufficient when the underlying value graph has cycles. On the other hand, we show that for general graphical valuations, auction formats, which rely on offering a bidder-specific price for each item and discounts for pairs of items, can guarantee efficiency. These results suggest that by exploiting the special graphical structure of valuations, it is possible to implement the efficient outcome using simple auction formats.

Bio: Ozan Candogan is a Ph.D. candidate in the Electrical Engineering and Computer Science Department of the Massachusetts Institute of Technology. He is also a member of the Laboratory for Information and Decision Systems. His research focuses on game theory, optimization, and mechanism design with applications to social and economic networks, e-commerce, and online markets. 

Ozan Candogan is also a recipient of the 2012 Microsoft Research Ph.D. fellowship, and 2009 Siebel Scholarship.

Vivienne Sze January 29
Vivienne Sze, Massachusetts Institute of Technology
"Parallel Algorithms and Architectures for Next Generation Video Coding"
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Abstract: Video compression has been critical to the prevalence of video in today’s society.  Today’s video codecs have both performance and power requirements.  High performance is needed to support high definition (HD) resolutions and frame rates, while low power is necessary to extend battery life for video playback/capture on portable devices such as smart phones and tablets.  As we look to the future, these requirements will become even more challenging.  Resolutions will continue to rise (from HD to Ultra-HD), and emerging applications such as Google glasses and video sensor networks will have more stringent power constraints. 

In this talk, we’ll discuss how parallelism can be effectively applied to address these demands.  Parallel processing can be used to increase the throughput for higher performance, which can be traded-off for lower power with voltage scaling.  First, we will describe how parallel architectures and aggressive voltage scaling were used in the design of a low power HD decoder that supports H.264/AVC, the most popular video coding standard on the market.  Next, we’ll discuss how joint optimization of algorithms and architectures can be used to address key bottlenecks to further increase throughput and reduce power, without sacrificing coding efficiency.  Finally, we’ll highlight several new parallel processing tools that were introduced to the latest video coding standard, High Efficiency Video Coding (HEVC), which was recently finalized in January 2013.

Bio: Vivienne Sze received the B.A.Sc. (Hons) degree in electrical engineering from the University of Toronto, Toronto, ON, Canada, in 2004, and the S.M. and Ph.D. degree in electrical engineering from the Massachusetts Institute of Technology (MIT), Cambridge, MA, in 2006 and 2010 respectively. She received the Jin-Au Kong Outstanding Doctoral Thesis Prize, awarded for the best PhD thesis in electrical engineering at MIT in 2011.

Since September 2010, she has been a Member of Technical Staff in the Systems and Applications R&D Center at Texas Instruments (TI), Dallas, TX, where she designs low-power algorithms and architectures for video coding. She also represents TI at the international JCT-VC standardization body developing HEVC, the next generation video coding standard. Within the committee, she is the primary coordinator of the core experiment on coefficient scanning and coding.

She was a recipient of the 2007 DAC/ISSCC Student Design Contest Award and a co-recipient of the 2008 A-SSCC Outstanding Design Award. She received the Natural Sciences and Engineering Research Council of Canada (NSERC) Julie Payette fellowship in 2004, the NSERC Postgraduate Scholarships in 2005 and 2007, and the Texas Instruments Graduate Woman's Fellowship for Leadership in Microelectronics in 2008.

Danielle S. Bassett

February 22
12:00 p.m., 337 Towne
Danielle S. Bassett, University of California, Santa Barbara
"Towards a Predictive Science of Network-Based Biological Systems"
Note: This is a joint seminar with the Department of Bioengineering

Read the Abstract
Many biological systems employ physically constrained networks of chemical, electrical, or mechanical signals to perform complex functions. Recent advances across multiple disciplines have begun to elucidate the role that these embedded networks play in guiding and enabling system dynamics. A critical remaining challenge is to harness the predictive role of complex networks in tissue, brain, and behavior to support the control, rescue, and imitation of system function. Such predictions can be extracted from network structure, network dynamics, or the properties of the signals that propagate through the network. I will illustrate these efforts and the associated mathematical tools they employ using examples drawn from material, biomedical and population systems. For example, the network structure of soft materials constrains sound propagation, informing the development of non-destructive testing and design techniques. The network dynamics of human brain activity predicts adaptive behaviors like learning, potentially enabling the monitoring of disease progression and rehabilitation. The information passed between individuals on a social network drives behavioral variability in the population, impacting information dissemination policies. I will discuss the ramifications of these findings for critical questions in bio- and systems engineering and outline some of the outstanding conceptual, experimental, and mathematical challenges that will propel research in the coming years.
March 12
11:00 a.m., 337 Towne
Firooz Aflatouni
"Electronic Photonic 1+1=3"
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Abstract: When we look at the long-term future of silicon electronics, it is apparent that the field will become increasingly inter-disciplinary. Despite great near/mid term research opportunities, it is necessary for the field to bridge the gap with other streams of science and engineering to grow further. I envision that the next several years will witness a great synergy between the fields of silicon electronics and photonic integrated circuits. It is not difficult to imagine that integrated electronic-photonic co-design will profoundly impact both fields resulting in advances in several areas such as communications, signal processing, imaging, and sensing.

Examples of Electronic-Photonic Co-Design may be categorized into two groups: (a) electronic assisted photonics, where analog, RF, mm-wave, and THz circuits are employed to improve the performance of photonic systems, and (b) photonic assisted electronics, where photonic systems and devices are used to improve the performance of the RF, mm-wave, and THz systems.

In this talk, as an example of electronic assisted photonics, I will present my work on RF assisted phase control of semiconductor lasers in both relative sense (RF assisted laser phased array) and absolute sense (RF assisted laser phase noise reduction) and will discuss its advantages and limitations. I will also present my work on integrated opto-electronic oscillators as an example of photonic assisted electronics.

Bio: Firooz Aflatouni received the M.S. and Ph.D. degrees in electrical engineering from the University of Southern California, Los Angeles, in 2005 and 2011, respectively. In 1999, he co-founded Pardis Bargh Company, where he was involved in the designing of inclined-orbit satellite tracking systems. From 2004 to 2006, he was a Design Engineer with MediaWorks Integrated Circuits Inc., Irvine, CA. He is currently a Post-doctoral Associate in the department of electrical engineering at the California Institute of Technology, Pasadena, CA. His research interests include RF-inspired photonics and low power RF, mm-wave, and THz integrated circuits. He was the recipient of the 2011 USC department of electrical engineering best Ph.D. thesis award, 2010 USC Ming Hsieh top 5 PhD student scholarship, 2010 NASA Tech Award for his work on development of a Ka-Band SiGe receiver front-end MMIC for space transponder applications, and the best B.S. thesis award for design and implementation of a non-geostationary satellite tracking system. He is the Silver medal winner of the nationwide Mathematics Olympiad in 1993.

March 18
Will Green
11:00 a.m., 337 Towne
"Ultra-Broadband Silicon Nanophotonics: From Exascale Computing to Mid-Infrared Sensing"
Read the Abstract and Bio

Abstract: Exascale high-performance computing systems are projected to become a reality by the end of the decade. Supercomputers of this size are anticipated to have considerable societal impact, by transforming scientific understanding of complex systems including global climate, brain neurophysiology, and fusion energy. Escalating computational performance and interconnection bandwidth significantly beyond today’s Petaflop systems will require deployment of hundreds of millions of optical links across all length scales within the system architecture, for interconnection of racks, modules, and individual chips. This talk will describe the device-level research behind IBM CMOS Integrated Silicon Nanophotonic technology, which realizes monolithic integration of deeply-scaled high-speed optical circuits within the front-end of a standard CMOS process. This platform can provide a cost-effective path toward the low-power, massively parallel optical transceivers required for Exascale systems.

While silicon optical interconnects utilize telecom-band wavelengths, the very same photonic integrated circuit platform can also be extended toward emerging applications within the mid-infrared spectrum. For example, we have engineered silicon’s high mid-infrared transmission, strong optical confinement, and low nonlinear absorption to generate nonlinear optical interactions 105 times larger than those found in optical fibers. This talk will highlight the recent development of several mid-infrared silicon nanophotonic components, including high-gain optical parametric amplifiers, tunable parametric oscillators, and supercontinuum sources. Such devices can play an essential role within mid-infrared molecular sensors for environmental monitoring, medical diagnostics, and threat detection.

Bio: Dr. William Green is a Research Staff Member at the IBM Thomas J. Watson Research Center. His research activities encompass the design of optical devices and integrated systems for terabit-per-second-class silicon nanophotonic interconnects. In addition, Dr. Green’s work has extended the silicon photonic integrated circuit platform to the generation and processing of mid-infrared optical signals, for various applications in molecular spectroscopy and sensing. The scientific impact of his work has been recognized within both the academic and industrial communities, through awards including the 2009 OSA Travelling Lecturer Award, the 2012 IBM Corporate Award, and the 2012 IEEE Photonics Society Young Investigator Award. Dr. Green has served on the technical committees for numerous OSA and IEEE conferences, and was Chair of the Nanophotonics Technical Sub-Committee for the IEEE Photonics Conference from 2009-2011. Dr. Green received his Ph.D. in Electrical Engineering from the California Institute of Technology in 2005, and the B.Sc. in Engineering Physics from the University of Alberta in 1999.

Boris Grot March 19
11:00 a.m., 337 Towne
Boris Grot, Parallel Systems Architecture Lab, EPFL
"Toward Data-Scalable Systems"
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Abstract: Big data is revolutionizing the way we live, work, and socialize. At the same time, big data is taxing our compute infrastructure in unprecedented ways. In many domains, data expansion rates are dwarfing the pace of technology improvement as measured by Moore’s law, challenging our ability to effectively store and process the data. Moreover, with the hardware industry hitting fundamental limits on its ability to lower operating voltages, energy requirements in big-data applications are skyrocketing. Sustaining the pressure of big data, and delivering on its promises, requires a fundamental restructuring of our compute infrastructure for data scalability.

In this talk, I will focus on data-intensive online applications, such as web search and social connectivity. I will explain how the mismatch between application demands and existing processor architectures leads to significant inefficiencies at the datacenter level. As a first step toward data-scalable systems, I will describe Scale-Out Processors, a processor design methodology and microarchitectural support for data-intensive online processing. By tuning the processor organization to the needs of the application domain, Scale-Out Processors improve datacenter performance by up to 7x within a fixed power budget versus state-of-the-art server processors.

Bio: Boris Grot is a post-doctoral researcher in the Parallel Systems Architecture Lab at EPFL. His research seeks to address efficiency bottlenecks and capability shortcomings of processing platforms for big data. Grot received his PhD in Computer Science from The University of Texas at Austin in 2011.

March 26
11:00 a.m., 337 Towne
Christoph Studer, Rice Unviersity
"Sparse Signal and Image Recovery: Theory, Algorithms, and VLSI Circuits"
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Abstract: Recent advances in theory, algorithm design, and very-large scale integration (VLSI) are accelerating progress in a host of important applications, such as signal processing, imaging, and wireless communication. Today's key challenge for the VLSI designer is to realize increasingly complicated algorithms that process massive amounts of data using cost-effective, low-power VLSI circuits and systems.

In this talk, I will advocate a holistic design approach that jointly considers the theory, algorithms, and VLSI implementation aspects to master this challenge. To highlight the efficacy of this approach, I will present two examples from my recent research on sparse signal recovery and compressive imaging. Specifically, I will introduce a novel mathematical framework that captures a large number of practical applications, including signal restoration, de-noising, in-painting, super-resolution, signal separation, and compressive sensing. Theoretical guarantees from this framework provide design guidelines for practical applications and enable the joint design of efficient algorithms and VLSI architectures. For both examples, I will present a range of application-specific integrated circuits (ASICs); one of these is destined for the recovery of static scenes acquired by the Rice single pixel camera (SPC). I will also introduce a novel video pipeline suitable for the reconstruction of dynamic scenes (videos) acquired by the SPC in short-wave infrared.

Bio:Christoph Studer received his MS and PhD degrees in Information Technology and Electrical Engineering from ETH Zurich, in 2005 and 2009, respectively. In 2005, he was a Visiting Researcher with the Smart Antennas Research Group at Stanford University. From 2006 to 2009, he was a Research Assistant in both the Integrated Systems Laboratory (IIS) and the Communication Technology Laboratory (CTL) at ETH Zurich. From 2009 to 2012, Dr. Studer was a Postdoctoral Researcher at CTL, ETH Zurich, and in the Digital Signal Processing Group at Rice University. Since 2013, he has held the position of Research Scientist at Rice University. Dr. Studer’s research interests include signal and image processing, the design of digital VLSI circuits and systems, and wireless communication.

Dr. Studer was the recipient of an ETH Medal in 2005 and 2011 for his MS and PhD theses, respectively. He has received best student paper awards at the 2007 Asilomar Conference on Signals, Systems, and Computers and the 2008 IEEE International Symposium on Circuits and Systems, and received the 2010 Swisscom/ICTnet Innovations Award. In 2011, Dr. Studer was awarded a two-year fellowship for Advanced Researchers by the Swiss National Science Foundation (SNSF).

March 26
12:15 p.m., 337 Towne
Lee C. Bassett, Center for Spintronics and Quantum Computation, University of California, Santa Barbara
"Harnessing the atom-like properties of single spins in diamond"

Read the Abstract

Abstract: The past decade has seen remarkable progress in the isolation and control of single spins in solid state devices. With electron spin coherence times in some materials now measured in seconds, single spins provide many features formerly unique to atomic systems in a form amenable to engineering complex integrated devices through semiconductor nanofabrication. In particular, the nitrogen-vacancy (NV) center in diamond has emerged as a promising single-spin system for wide-ranging applications in quantum computing, quantum communication, and nanoscale sensing. The NV center’s electronic spin can be initialized and measured optically, has millisecond coherence times at room temperature, and it provides access to individual nuclear spins with even better coherence properties. Recently, we have developed several techniques to control the NV center’s spin using coherent light-matter interactions – protocols that can be used to access other spin systems that lack the NV center’s unique optical addressability but might offer desirable properties for other applications. I will review the current state of this exciting field, describe several of our recent experiments, and outline the challenges and possibilities for the road ahead.

  April 5
10:30 a.m., 337 Towne
Jonathan Fan, University of Illinois at Urbana-Champaign
"Soft Electronic and Electromagnetic Systems for Biomedical Device Integration"
Read the Abstract and Bio

Abstract:Electronic and electromagnetic devices that are mechanically soft provide a foundation for new technological interfaces with the body. In this talk, I will present research on “epidermal electronics.” This technology consists of thin films of electronic materials that have mechanical properties matching skin, similar to a temporary transfer tattoo. I will focus on two topics. The first is on the use of fractals as a general design tool for constructing devices with novel mechanical and electronic properties. With these design criteria, I demonstrate multi-functional devices that integrate electrode, temperature sensor, and heater capabilities. The second is on the development of stretchable antennas, which are tunable in frequency and which can be used for wireless power harvesting and communications.

Bio:Jonathan Fan is currently a Beckman Postdoctoral Fellow at the University of Illinois, Urbana-Champaign, where he is working with Professors John Rogers on new photonic and electronic device platforms. He received his doctorate in applied physics from Harvard University in 2010, where he was an NSF Graduate Fellow and did plasmonics research in colloidal systems and in quantum cascade laser design with Professor Federico Capasso. He received his BS with highest honors in electrical engineering from Princeton University in 2004.

April 11
10:00 a.m., 307 Levine
Han Wang, MIT
"2D Materials, Devices and Systems: A New Paradigm for Electronics and Optoelectronics"
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Abstract:In the past eight years, the research community has seen rapidly growing interests in two-dimensional (2D) crystals and their applications. The 2D carrier confinement in this versatile family of materials - whose members range from the well-known semi-metal graphene to the insulator boron nitride, or the semiconducting layered transition metal dichalcogenides (LTMD) - confers to them unique band structures with correlated electronic states where charge, spin, orbital, valley and lattice degrees of freedom play an important role in defining their exceptional properties of carrier transport, tunable bandgaps, mechanical strength, piezoelectricity, thermoelectric effects and their interactions with light. These materials, still in their infancy, carry great potential to redefine nano-electronics, optoelectronics and their interaction with biological systems in the coming years. In this talk, I will present my work on understanding the material synthesis, device technology, carrier transport and the forward-looking engineering efforts to develop electronic applications based on 2D crystals at the device and circuit level. I will conclude with remarks on how these new materials are expected to change energy generation, biological sensors, medical electronics at both device and system levels.

Bio:Han Wang received the B.A. and M.Eng. degrees in electrical and information science, both with highest honors, from Cambridge University, England, in 2007 and 2008. He is currently pursuing the Ph.D. degree in Electrical Engineering and Computer Science at Massachusetts Institute of Technology (MIT). In summer 2012, he held an internship at IBM T. J. Watson Research Center. His research interests include the synthesis, device technology and novel circuit applications of two-dimensional (2D) materials – including graphene, hBN, MoS2, WS2, etc., and their heterostructures – with emphasis on exploring both the fundamental understanding and forward-looking applications of 2D materials in ubiquitous electronics, optoelectronics, energy efficient applications, and interaction with biological systems. His past research also includes GaN-based III-V HEMTs for high power millimeter-wave applications and Si power electronic devices.

His work has been recognized with multiple awards including Cambridge University Agilent Prize, International Conference on Compound Semiconductor Manufacturing Technology (CS MANTECH) Best Student Paper Award and numerous fellowships. Mr. Wang has authored or coauthored more than 40 publications in distinguished journals and conferences, 8 of them invited, 1 book chapter and 1 patent.

  May 2
2:00 p.m., 337 Towne
Jie Fu, Ph.D. Candidate, University of Delaware
"Adaptive Symbolic Control with Grammatical Inference"
Read the Abstract and Bio

Abstract:While abstraction methods and solutions in algorithmic game theory exist for symbolic control of some classes of dynamical systems, problems may arise when the system interacts with an unknown, dynamical, and possibly adversarial environment, or the occurrence of any unknown factor that makes the existing model no longer valid.; Without making assumptions on the unknown factor, one possible solution is to incorporate learning with control design, as done in the context of reinforcement learning. Essentially, reinforcement learning is about learning how to control for a given objective. Alternatively, we consider another problem: is it possible to build and refine on-line a model that accounts for the unknown factors? The question is motivated by the idea of separating learning from control design, which is novel. In this talk, we answer the question in affirmative by introducing grammatical inference as a system identification method into symbolic control design. The key observation is that at the abstraction level both the system and its environment are formal objects, e.g. automata, languages, etc. In this sense, grammatical inference for formal object identification can be applied to correct or rebuild the model of the actual system. We present a general framework, which is provably efficient and correct, adapting and improving the controller with knowledge inferred from observations using grammatical inference. Extensions to other cases, for example, adaptive control design with partial observation, will be discussed.

Bio:Jie Fu is a Ph.D. student in Dr. Herbert Tanner's research group in the Department of Mechanical Engineering at the University of Delaware and is expected to complete her Ph.D. at UDel in 2014. Her research is mainly focused on abstraction and bottom-up symbolic control design for hybrid systems, the integration of learning theory and algorithmic game theory in adaptive symbolic control synthesis, and game theoretic analysis for mechanism design and symbolic planing in multi-agent systems.