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SUNMONTUEWEDTHUFRISAT
Conferences, Lectures, & Seminars
Events for March
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MHI Distinguished Visitor Talk
Wed, Mar 02, 2016 @ 10:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Prof. K.J. Ray Liu, University of Maryland
Talk Title: Why Time-Reversal for Future 5G Wireless?
Abstract: Time reversal is a fundamental physical phenomenon that takes advantage of unavoidable but rich multi-paths in radio propagation to create the spatial-temporal resonance effect, the so-called focusing effect. One can image that the larger the transmission power, the more observable multipaths. When the power is fixed, so does the maximum number of observable multipaths. Since radio waves travel at the speed of light, for one to see the multipath profile in detail, it needs high resolution in time, which implies very broad bandwidth in frequency. The larger the bandwidth, the better the time resolution, and therefore the more multipaths can be revealed. In essence, multipaths are naturally existing 'degrees of freedom' ready to be harvested via power and bandwidth. In a real environment, especially indoors, depending on the structure of the buildings, the number of observable multipaths can one observe is around 15-30 significant multipaths with 150 MHz bandwidth - the entire ISM band at 5.8 GHz. Such a large number of degrees of freedom, existing in nature, can be harvested to enable engineering applications. In this talk, we will argue that time-reversal is an ideal platform for future 5G wireless because it realizes the massive multipath effect by using a single antenna and has low complexity as the environment is serving as the computer. It is highly secure and energy efficient, scalable for extreme network densification, and ideal for cloud-based radio networks. It also offers very simply but high resolution for indoor positioning systems, an essential property for Internet of Things applications. Time-reversal meets all the demands one can envision for future 5G wireless!
Biography: Dr. K. J. Ray Liu was named a Distinguished Scholar-Teacher of University of Maryland, College Park, in 2007, where he is Christine Kim Eminent Professor of Information Technology. He leads the Maryland Signals and Information Group conducting research encompassing broad areas of information and communications technology with recent focus on future wireless technologies, network science, and information forensics and security. Dr. Liu was a recipient of the 2016 IEEE Leon K. Kirchmayer Technical Field Award on graduate teaching and mentoring, IEEE Signal Processing Society 2014 Society Award, IEEE Signal Processing Society 2009 Technical Achievement Award, and various best paper awards. Recognized by Thomson Reuters as a Highly Cited Researcher, he is a Fellow of IEEE and AAAS. Dr. Liu is a member of IEEE Board of Director. He was President of IEEE Signal Processing Society, where he has served as Vice President -“ Publications and the Editor-in-Chief of IEEE Signal Processing Magazine. He also received teaching and research recognitions from University of Maryland including university-level Invention of the Year Award (three times); and college-level Poole and Kent Senior Faculty Teaching Award, Outstanding Faculty Research Award, and Outstanding Faculty Service Award, all from A. James Clark School of Engineering (one award each per year from the entire college).
Host: Prof. Shrikanth Narayanan & Prof. C.-C. Jay Kuo
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Tanya Acevedo-Lam/EE-Systems
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Communications, Networks & Systems (CommNetS) Seminar
Wed, Mar 02, 2016 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Gregory Valiant, Stanford University
Talk Title: When your big data seems too small: accurate inferences beyond the empirical distribution
Series: CommNetS
Abstract: We discuss two problems related to the general challenge of making accurate inferences about a complex distribution, in the regime in which the amount of data (i.e the sample size) is too small for the empirical distribution of the samples to be an accurate representation of the underlying distribution. The first problem is the basic task of learning a discrete distribution, given access to independent draws. We show that one can accurately recover the unlabelled vector of probabilities of all domain elements whose true probability is greater than 1/(n log n). Stated differently, one can learn-“up to relabelling-“the portion of the distribution consisting of elements with probability greater than 1/(n log n). This result has several curious implications, including leading to an optimal algorithm for "de-noising" the empirical distribution of the samples, and implying that one can accurately estimate the number of new domain elements that would be seen given a new larger sample, of size up to n * log n. (Extrapolation beyond this sample size is provable information theoretically impossible, without additional assumptions on the distribution.) While these results are applicable generally, we highlight an adaptation of this general approach to some problems in genomics (e.g. quantifying the number of unobserved protein coding variants).
The second problem we consider is the task of accurately estimating the eigenvalues of the covariance matrix of a (high dimensional real-valued) distribution-“the "population spectrum". (These eigenvalues contain basic information about the distribution, including the presence or lack of low-dimensional structure in the distribution and the applicability of many higher-level machine learning and multivariate statistical tools.) As we show, even in the regime where the sample size is linear or sublinear in the dimensionality of the distribution, and hence the eigenvalues and eigenvectors of the empirical covariance matrix are misleading, accurate approximations to the true population spectrum are possible.
This talk is based on three papers, which are joint works with Paul Valiant, with Paul Valiant and James Zou, and with Weihao Kong.
Biography: Greg Valiant joined the Computer Science Department at Stanford as an Assistant Professor in Fall 2013, after completing a postdoc at Microsoft Research, New England. His main research interests are in algorithms, learning, applied probability and statistics; he is also interested in game theory, and has enjoyed working on problems in database theory. Valiant graduated from Harvard with a BA in Math and an MS in Computer Science, and obtained his PhD in Computer Science from UC Berkeley in 2012.
Host: Dr. Mahdi Soltanolkotabi
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Annie Yu
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
MHI Distinguished Visitor Talk
Thu, Mar 03, 2016 @ 10:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Prof. K.J. Ray Liu, University of Maryland
Talk Title: Learning with Strategic Decision Making in Social Media
Abstract: With the increasing ubiquity and power of mobile devices, as well as the prevalence of social media, more and more activities in our daily life are being recorded, tracked, and shared, creating the notion of 'social media'. Such abundant and still growing real life data, known as 'big data', provide a tremendous research opportunity in many fields. To analyze, learn and understand such user generated big data, machine learning has been an important tool and various machine learning algorithms have been developed. However, since the user generated big data is the outcome of users decisions, actions and their socio economic interactions, which are highly dynamic, without considering users local behaviors and interests, existing learning approaches tend to focus on optimizing a global objective function at the macroeconomic level, while totally ignore users local decisions at the microeconomic level. As such there is a growing need in bridging machine/social learning with strategic decision making, which are two traditionally distinct research disciplines, to be able to jointly consider both global phenomenon and local effects to understand/model/analyze better the newly arising issues in the emerging social media. In this talk, we present the notion of 'decision learning that can involve users behaviors and interactions by combining learning with strategic decision making. We will discuss some examples from social media with real data to show how decision learning can be used to better analyze users optimal decision from a user perspective as well as design a mechanism from the system designers perspective to achieve a desirable outcome.
Biography: Dr. K. J. Ray Liu was named a Distinguished Scholar-Teacher of University of Maryland, College Park, in 2007, where he is Christine Kim Eminent Professor of Information Technology. He leads the Maryland Signals and Information Group conducting research encompassing broad areas of information and communications technology with recent focus on future wireless technologies, network science, and information forensics and security. Dr. Liu was a recipient of the 2016 IEEE Leon K. Kirchmayer Technical Field Award on graduate teaching and mentoring, IEEE Signal Processing Society 2014 Society Award, IEEE Signal Processing Society 2009 Technical Achievement Award, and various best paper awards. Recognized by Thomson Reuters as a Highly Cited Researcher, he is a Fellow of IEEE and AAAS. Dr. Liu is a member of IEEE Board of Director. He was President of IEEE Signal Processing Society, where he has served as Vice President -“ Publications and Board of Governor. He was the Editor-in-Chief of IEEE Signal Processing Magazine. He also received teaching and research recognitions from University of Maryland including university-level Invention of the Year Award; and college-level Poole and Kent Senior Faculty Teaching Award, Outstanding Faculty Research Award, and Outstanding Faculty Service Award, all from A. James Clark School of Engineering.
Host: Prof. Shrikanth Narayanan & Prof. C.-C. Jay Kuo
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Tanya Acevedo-Lam/EE-Systems
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Less Talking, More Learning: Avoiding Coordination In Parallel Machine Learning Algorithms
Thu, Mar 03, 2016 @ 01:30 PM - 02:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Dimitris Papailiopoulos, Postdoctoral Researcher/UC Berkeley
Talk Title: Less Talking, More Learning: Avoiding Coordination In Parallel Machine Learning Algorithms
Abstract: The recent success of machine learning (ML) in both science and industry has generated an increasing demand to support ML algorithms at scale. In this talk, I will discuss strategies to gracefully scale machine learning on modern parallel computational platforms. A common approach to such scaling is coordination-free parallel algorithms, where individual processors run independently without communication, thus maximizing the time they compute. However, analyzing the performance of these algorithms can be challenging, as they often introduce race conditions and synchronization problems.
In this talk, I will introduce a general methodology for analyzing asynchronous parallel algorithms. The key idea is to model the effects of core asynchrony as noise in the algorithmic input. This allows us to understand the performance of several popular asynchronous machine learning approaches, and to determine when asynchrony effects might overwhelm them. To overcome these effects, I will propose a new framework for parallelizing ML algorithms, where all memory conflicts and race conditions can be completely avoided. I will discuss the implementation of these ideas in practice, and demonstrate that they outperform the state-of-the-art across a large number of machine learning tasks.
Biography: Dimitris Papailiopoulos is a postdoctoral researcher in the Department of Electrical Engineering and Computer Sciences at UC Berkeley and a member of the AMPLab. His research interests span machine learning, coding theory, and parallel and distributed algorithms, with a current focus on coordination-free parallel machine learning, large-scale data and graph analytics, and the use of codes to speed up distributed computation. Dimitris completed his Ph.D. in electrical and computer engineering at UT Austin in 2014. At Austin he worked under the supervision of Alex Dimakis. In 2015, he received the IEEE Signal Processing Society, Young Author Best Paper Award.
Host: Professor Keith Chugg, chugg@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
EE-EP Seminar - Jun-Chau Chien, Friday, March 4th in EEB 132 at 2:00pm
Fri, Mar 04, 2016 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Jun-Chau Chien, University of California, Berkeley
Talk Title: mm-Wave Lab-on-CMOS: Electromagnetic Sensing from Micro-to Nano-scales
Abstract: Lab-on-CMOS is an emerging platform for Point-of-Care diagnostics and precision medicine. By directly integrating active CMOS electronics into passive Lab-on-Chip devices, the new System-on-Chip not only offers ultimate device miniaturization but also enables highly integrated multiphysics biosensing and actuation. This research addresses the challenges in such a hybrid system while embracing the opportunities in system co-design to achieve improved sensing performance that leads to new scientific findings.
In this talk, I will present my research on a Lab-on-CMOS dielectric spectrometer for single-cell analysis using near-field sensing at millimeter-wave (mm-Wave) frequencies. The aim is to understand the wideband electromagnetic signatures at cellular and molecular levels and to open its way for real-time and label-free medical diagnostics and biological studies. I will focus on innovations in circuits, systems, microfluidics, and calibration techniques to enable a capacitance equivalent sensitivity limit of sub-aF, suitable for large-scale characterization of single-cell dielectric spectroscopy (6.5 ~ 30 GHz) in the setting of high-throughput flow cytometry. The capability of cell sorting based on frequency dispersion is demonstrated with the measurements of human breast cancer cells. In addition to electromagnetic sensing, I will introduce multiphysics actuation techniques to quantify the mechanical property of the cells. Specifically, the system measures the deformation of cells using hydrodynamic stretching. I will also discuss the challenges in sensing toward nano-scales and sub-THz frequencies and present an on-chip single-element electronic calibration (E-Cal) technique for nano-device measurements. In the end, I will conclude my talk with Lab-on-CMOS technology for new applications in sensing, imaging, and communication.
Biography: Jun-Chau Chien received the B.S. and M.S. degrees in Electrical Engineering from National Taiwan University in 2004 and 2006, respectively, and the Ph.D. degree in Electrical Engineering and Computer Sciences from University of California, Berkeley, in 2015. He is currently a post-doctoral research associate at University of California, Berkeley. He has held industrial positions at InvenSense, Xilinx, and HMicro working on mixed-signal integrated circuits for inertial sensors and wireline/wireless transceivers. He is broadly interested in innovative biotechnology for point-of-care diagnostics and medical imaging with emphasis on silicon-based approaches.
Dr. Chien is the recipient of the 2006 Annual Best Thesis Award from Graduate Institute of Electronics Engineering, National Taiwan University, the 2007 International Solid-State Circuit Conference (ISSCC) Silkroad Award, the co-recipient of 2010 IEEE Jack Kilby Award for ISSCC Outstanding Student Paper, the 2014 Analog Devices Outstanding Design Award, the 2014 Microwave Theory and Techniques Society (MTT-S) Graduate Fellowship for Medical Applications, the 2014 Solid-State Circuit Society (SSCS) Predoctoral Achievement Award, and the 2014 UC Berkeley Outstanding Graduate Student Instructor Award.
Host: EE-Electrophysics
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
A Network-Centric Approach To Data Science: From Distributed Learning To Social Recommender Systems
Mon, Mar 07, 2016 @ 10:30 AM - 11:30 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Zhenming Liu, Princeton University
Talk Title: A Network-Centric Approach To Data Science: From Distributed Learning To Social Recommender Systems
Abstract: Networks play important roles in various stages of a data science life cycle, including the design of scalable platforms, the collection of data, and the analysis of statistical models. I will talk about my efforts to develop a suite of network-based techniques in these stages. After briefly describing my work on designing scalable platforms for online machine learning algorithms and that for sampling data from the Web, I will discuss the details of a recent project that uses network analysis to study social recommender systems. A social recommender system leverages its users social connections to improve recommendation service. The recommender system we have designed simultaneously maximizes (a) an individuals benefit from using a social network and (b) the networks efficiency in disseminating information. The design solution brings together techniques from spectral analysis, random walk theory, and large-scale optimization.
Biography: Zhenming Liu received his PhD from Harvard University (working with Michael Mitzenmacher) and then spent two years as a postdoc at Princeton University (primarily working with Mung Chiang and Jennifer Rexford). Presently, he is a machine learning researcher for a quantitative hedge fund. Dr. Liu's research focus is the intersection of data science and network analysis; he designs both algorithms that analyze network structures inherent in the data (e.g., social and biological networks) and scalable platforms in support of big data analytics. He has received several awards for his research, including a Best Paper Runner Up at INFOCOM 2015 and a Best Student Paper Award at ECML/PKDD 2010.
Host: Professor Bhaskar Krishnamachari
Location: 248
Audiences: Everyone Is Invited
Contact: Theodore Low
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
EE-EP Seminar - Mona Zebarjadi, Monday, March 7th in EEB 132 @ 2:00pm
Mon, Mar 07, 2016 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Mona Zebarjadi, Rutgers University
Talk Title: Manipulation of Electricity and Heat at Nanoscales
Abstract: Fundamental understanding of electron and phonon transport enables us to manipulate electricity and heat at nanoscales. Advances in computations and in parallel in nanotechnology, allow design of specific quantum potentials inside materials and devices to guide charge and heat carriers. The resulting capability of manipulating electricity and heat inspires design of new electronic devices, power generators, and heat pumps. In this talk, I will discuss several examples to elucidate our approach. First I will discuss novel strategies to enhance materials carrier mobility and conductivity for design of fast transistors, switches, and thermoelectric modules via un-conventional doping schemes including 3D modulation-doping and invisible-doping. Transport modeling and experimental results on single layer graphene will be presented next as a design example of active and passive coolers. Finally, design of solid-state thermionic coolers in micron-scales (using Monte-Carlo simulations) as well as nano-scales (using first-principles modeling approach) will be described.
Biography: Mona Zebarjadi is a professor of mechanical engineering at Rutgers University. Her research interests are in electron and phonon transport modeling; materials and device design, fabrication and characterization; with emphasis on energy conversion systems such as thermoelectric, thermionic, and thermomagnetic power generators, and heat management in high power electronics and optoelectronic devices. She received her Bachelor's degree in physics from Sharif University in 2004 and her PhD in EE from UCSC in 2009, after which she spent 3 years at MIT as a postdoctoral fellow working jointly with electrical and mechanical engineering departments. She joined Rutgers University in January 2013. She is the recipient of 2014 AFOSR career award, 2015 A.W. Tyson assistant professorship award, MRS graduate student gold medal, and SWE electronics for imaging scholarship.
Host: EE-Electrophysics
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
EE 598 Cyber-Physical Systems Seminar Series
Mon, Mar 07, 2016 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Saman Zonouz, Assistant Professor at Rutgers University
Talk Title: Trustworthy Critical Infrastructures Threats, Challenges, and Countermeasures Applications
Abstract: Critical cyber-physical infrastructures, such as the power grid, integrate networks of computational and physical processes to provide the people across the globe with essential functionalities and services. Protecting these critical infrastructures is a vital necessity because the failure of these systems would have a debilitating impact on economic security and public health and safety. Our research and development projects aim at provision of real-world solutions to facilitate the secure and reliable operation of next-generation critical infrastructures and require interdisciplinary research efforts across adaptive systems and network security, cyber-physical systems, and trustworthy real-time detection and response mechanisms. In this talk, I will focus on real past and potential future threats against critical infrastructures and embedded devices, and discuss the challenges in design, implementation, and analysis of security solutions to protect cyber-physical platforms. I will introduce novel classes of working systems that we have developed to overcome these challenges in practice, and finally conclude with several concrete directions for future research.
Biography: Saman Zonouz is an Assistant Professor in the Electrical and Computer Engineering Department at Rutgers University since September 2014 and the Director of the 4N6 Cyber Security and Forensics Laboratory. His research has been awarded NSF CAREER Award in 2015, Google Security Reward in 2015, Top-3 Demo at IEEE SmartGridComm 2015, the Faculty Fellowship Award by AFOSR in 2013, the Best Student Paper Award at IEEE SmartGridComm 2013, the University EARLY CAREER Research award in 2012 as well as the Provost Research Award in 2011. The 4N6 research is currently supported by National Science Foundation (NSF), Department of Homeland Security (DHS), Office of Naval Research (ONR), Department of Energy (DOE), Advanced Research Projects Agency Energy (ARPA-E), Department of Education (DOE), Siemens Research Labs (SRL), WinRiver, GrammaTech, Google, and Fortinet Corporation including tech-to-market initiatives. Saman's current research focuses on systems security and privacy, trustworthy cyber-physical critical infrastructures, binary/malware analysis and reverse engineering, as well as adaptive intrusion tolerance architectures. Saman has served as the chair, program committee member, guest editor and a reviewer for top international conferences and journals. Saman serves on Editorial Board for IEEE Transactions on Smart Grid. He obtained his Ph.D. in Computer Science, specifically, intrusion tolerance architectures for the cyber-physical infrastructures, from the University of Illinois at Urbana-Champaign in 2011.
Host: Paul Bogdan
Location: 248
Audiences: Everyone Is Invited
Contact: Estela Lopez
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
From Communication to Sensing and Learning: An Information Theoretic Perspective
Wed, Mar 09, 2016 @ 10:00 AM - 11:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Hamed Hassani, Postdoctoral Scholar/ETH Zurich
Talk Title: From Communication to Sensing and Learning: An Information Theoretic Perspective
Abstract: We are witnessing a new era of science -” ushered in by our ability to collect massive amounts of data and by unprecedented ways to learn about the physical world. Beyond the challenges of storage and communication, there are new frontiers in the acquisition, analysis and exploration of data. In this talk, I will view these frontiers through the lens of information theory. I will argue that information theory lies at the center of data science, offering insights beyond its classical applications. As a concrete example, I will consider the problem of optimal data acquisition, a challenge that arises in active learning, optimal sensing and experimental design. Based on information theoretic foundations, and equipped with tools from submodular optimization theory, I will present a rigorous analysis of the widely-used sequential information maximization policy (also known as the information-gain heuristic). Our analysis establishes conditions under which this policy provably works near-optimally and identifies situations where the policy fails. In the latter case, our framework suggests novel, efficient surrogate objectives and algorithms that outperform classical techniques.
Biography: Hamed Hassani is a post-doctoral scholar at the Institute for Machine Learning at ETH Zurich. He received a Ph.D. degree in Computer and Communication Sciences from EPFL, Lausanne. Prior to that, he received a B.Sc. degree in Electrical Engineering and a B.Sc. degree in Mathematics from Sharif University of Technology, Tehran. Hamed's fields of interest include machine learning, coding and information theory as well as theory and applications of graphical models. He is the recipient of the 2014 IEEE Information Theory Society Thomas M. Cover Dissertation Award. His co-authored paper at NIPS 2015 was selected for an oral (plenary) presentation, and his co-authored paper at ISIT 2015 received the IEEE Jack Keil Wolf ISIT Student Paper Award.
Host: Professor Urbashi Mitra, ubli@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Computational Imaging for Real-Time Gigapixel and 3D Wave-Field Microscopy
Wed, Mar 09, 2016 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Lei Tian, Postdoctoral Associate / Dept of EECS, University of California, Berkeley
Talk Title: Computational Imaging for Real-Time Gigapixel and 3D Wave-Field Microscopy
Abstract: Abstract: Computational imaging is a new frontier of imaging technology that overcomes fundamental limitations of conventional systems by jointly designing optics, devices, signal processing, and algorithms. In this talk, I will present recent advancements in computational wave-field imaging that enable Gigapixel and 3D phase microscopy capability, breaking the limit of space-time-bandwidth product in traditional systems. In particular, I will describe a computational microscopy platform that implements coded illumination and nonlinear phase retrieval algorithms to reconstruct wide field-of-view and high-resolution phase images. Further, new illumination multiplexing techniques reduce data requirements by one order of magnitude, and acquisition times from minutes to sub-second. Experiments demonstrate quantitative dynamic imaging of rare biological events across multiple scales in both space and time. Finally, new 3D wave-optical model and reconstruction technique allow Gigavoxel reconstruction of 3D objects, achieving lateral resolution and depth sectioning well beyond the physical limit of traditional systems. Such computational imaging approach creates significant new capabilities by integrating hardware and computation at the system level. It promises wide applications, such as biomedicine, metrology, inspection, security and X-ray.
Biography: Bio: Lei Tian is a postdoctoral associate in the department of Electrical Engineering and Computer Sciences at University of California Berkeley. He received his Ph.D. in 2013 and M.S. in 2010, both from Massachusetts Institute of Technology (MIT). His research interests include computational imaging, computational-optical instrumentation, phase retrieval, imaging through 3D complex media, large-scale microscopy, and their applications in biomedicine, security, metrology, inspection, X-ray and EUV.
Dr. Tian is the author of over 30 peer-reviewed articles and is a named inventor on 3 US patent applications. His recent work on coded illumination for Gigapixel imaging was awarded the Best Paper in Optical Society of America (OSA) Imaging Systems and Applications conference (2014). His work on optical coherence recovery using low-rank method was awarded the Emil Wolf Best Student Paper in OSA Frontier in Optics annual meeting (2011). Dr. Tian is currently serving as conference chair and program committee member in multiple conferences of OSA, SPIE, and IEEE.
Host: Dr. Justin Haldar, jhaldar@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Communications, Networks & Systems (CommNetS) Seminar
Wed, Mar 09, 2016 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Na Li, Harvard University
Talk Title: Distributed Energy Management with Limited Communication
Series: CommNetS
Abstract: A major issue in future smart grid is how intelligent devices and independent producers can respectively change their power consumption/production to achieve near maximum efficiency for the power network. Limited communications between devices, producers etc. necessitates an approach where the elements of the network can act in an autonomous manner with limited information/communications yet achieve near optimal performance. In this talk, I will present our recent work on distributed energy management with limited communication. In particular, I will show how we can extract information from physical measurements and recover information from local computation. We will investigate the minimum amount of communication for achieving the optimal energy management and study how limited communication affects the convergence rate of the distributed algorithms.
Biography: Na Li is an assistant professor in Electrical Engineering and Applied Mathematics of the School of Engineering and Applied Sciences in Harvard University since 2014. She received her PhD degree in Control and Dynamical systems from California Institute of Technology in 2013 and was a postdoctoral associate of the Laboratory for Information and Decision Systems at Massachusetts Institute of Technology. Her research lies in the design, analysis, optimization and control of distributed network systems, with particular applications to power networks. She received NSF career award (2016) and entered the Best Student Paper Award ï¬nalist in the 2011 IEEE Conference on Decision and Control.
Host: Prof. Ashutosh Nayyar
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Annie Yu
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Inferring Network Internal State via Network Tomography
Thu, Mar 10, 2016 @ 10:30 AM - 11:30 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Ting He, IBM
Talk Title: Inferring Network Internal State via Network Tomography
Abstract: Timely and accurate knowledge of network internal state (e.g., delay/loss/jitter on links) is essential to efficient network operation and resource allocation. Obtaining such knowledge is, however, a highly nontrivial task in large-scale heterogeneous networks, where the existence of heterogeneous domains due to the difference in communication technology, protocol, ownership, and/or policy makes it difficult for a single monitoring system to receive global support throughout the network.
In this talk, I will review a promising approach for monitoring such networks by inferring the internal network state (e.g., link delay) from end-to-end measurements (e.g., path delay) taken between monitors, known as network tomography. The focus will be given to a key challenge in applying network tomography, called "lack of identifiability", i.e., the measurements cannot uniquely determine the network state. In contrast to previous works that resort to best-effort heuristics, I aim at guaranteeing identifiability via carefully designed measurements. Specifically, I (i) establish the fundamental condition on the network topology and monitor placement to achieve identifiability, (ii) develop the optimal monitor placement algorithm that guarantees identifiability using a minimum number of monitors, (iii) develop an efficient path construction algorithm that finds a set of linearly independent paths, whose measurements can uniquely determine the link metrics, and (iv) design probing experiments that allocate probes among the paths to minimize the error in estimating link parameters in the case of random link metrics. The above results are selected from publications at ICDCS'13, IMC'13, TON'14, and SIGMETRICS'15, and have won several best paper awards and nomination.
Biography: Ting He is a Research Staff Member at IBM T.J. Watson Research Center, where she has worked for over 8 years in the Wireless Network Research Group and the Network Analytics Research Group. Before that, she was a Graduate Research Assistant at the Adaptive Communications and Signal Processing Group at Cornell University in 2003-2007, where she received the Ph.D. degree in Electrical Engineering.
At IBM, Dr. He has worked as a primary researcher and task lead in several major research programs including the International Technology Alliance (ITA) program funded by US ARL and UK MoD, the Measurement Science in Cloud Computing program funded by NIST, and the Social Media in Strategic Communication (SMISC) program funded by DARPA. Her work aims at applying mathematical principles developed in signal processing, graph theory, information theory, stochastic optimization, and online learning to practical problems arising in the broad areas of network monitoring, performance analysis, and optimization.
Dr. He is a senior member of IEEE. She has served as the Membership Co-chair of ACM N2Women and the TPC of many communications and networking conferences, including IEEE INFOCOM, IEEE SECON, IEEE/ACM IWQoS, IEEE WiOpt, IEEE MILCOM, IEEE ICNC, IFIP Networking, etc. She received the Outstanding Contributor Award from IBM Research in 2009 and 2013, and the Most Collaboratively Complete Publications Award from ITA in 2015. Her papers won the Best Paper Award at IEEE ICDCS'13, the Outstanding Student Paper Award at ACM SIGMETRICS'15, the Best Paper Nomminee at ACM IMC'13, and the Best Student Paper Award at IEEE ICASSP'05. She received the Distinguished TPC Member Award for her service at IEEE INFOCOM'16. In school, she was an Outstanding College Graduate of Beijing and and an Outstanding Gradudate of Peking University in 2003, and a winner of the Excellent Student Awards and scholarships from Peking University from 1999 to 2002.
Host: Professor Bhaskar Krishnamachari
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Theodore Low
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Munushian Seminar - Mark Lundstrom, Friday, March 11th at 2:00pm in EEB 132
Fri, Mar 11, 2016 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Mark Lundstrom, Purdue University
Talk Title: Electrons and Phonons in Nanodevices
Abstract: The theory of electron transport in semiconductors has developed, evolved, and matured alongside the development of semiconductor technology from microelectronics to nanoelectronics. The field of thermal transport has an even longer history beginning with Fourier's Law, but electrons and phonons always go together - sometimes it is a problem, as in the self-heating of electronic devices, and sometimes it is the whole point, as in thermoelectrics. My goal in this talk is to discuss the remarkably simple conceptual picture of electron transport at the nanoscale that has emerged from decades of work on experiments and sophisticated transport theory and simulations and to explore its application to thermal transport. Two central concepts are the Landauer approach and the McKelvey-Shockley two-flux form of the Boltzmann equation. I'll discuss the similarities and differences of electron and phonon transport and some new insights into thermal transport that come from using concepts from electronics. Finally, I'll identify some issues that need to be addressed if we are to develop the comprehensive conceptual and computational framework for electrothermal transport that is needed to describe modern nanodevices.
Biography: Mark Lundstrom is the Don and Carol Scifres Distinguished Professor of Electrical and Computer Engineering at Purdue University. He received Ph.D. from Purdue University in 1980 and BEE and MSEE degrees from the University of Minnesota in 1973 and 1974. Between his MSEE and Ph.D. degrees, he worked at Hewlett-Packard Corporation on integrated circuit process development and manufacturing. At Purdue, his research has explored a wide range of semiconductor devices, the physics of carrier transport, and the modeling and numerical simulation of devices. His current focus is on energy conversion devices such as solar cells and thermoelectric devices and on the physics of the ultimate transistor. Lundstrom was the founding director of the Network for Computational Nanotechnology and nanoHUB.org, a science gateway that now serves a worldwide nanotechnology community of more than 300,000 individuals. He currently leads NEEDS, an NSF and industry-funded, multi-university initiative focused on new-era electronics, and he leads the nanoHUB-U initiative for on-line education. Dr. Lundstrom is a fellow of the Institute of Electrical and Electronic Engineers (IEEE), the American Physical Society, and the American Association for the Advancement of Science (AAAS). He has received several awards for his teaching and research, and is a member of the U.S. National Academy of Engineering.
Host: EE-Electrophysics
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Anthropomorphic Digital Reference Objects: Extensible Tools for Evaluating Quantitative Imaging Algorithms
Fri, Mar 18, 2016 @ 10:30 AM - 11:30 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Ryan Bosca , University of Wisconsin
Talk Title: Anthropomorphic Digital Reference Objects: Extensible Tools for Evaluating Quantitative Imaging Algorithms
Series: Medical Imaging Seminar Series
Abstract: Assessing and mitigating the various sources of bias and variance associated with MR image quantification algorithms (e.g., pharmacokinetic modeling of dynamic contrast enhanced MRI) is essential to the use of such algorithms in clinical research and practice. Grid based digital reference objects (DRO) have been used traditionally to assess such algorithms. More recently, a number of publicly available, normal patient derived, digital anthropomorphic tissue models have been developed. By assigning physical parameters to these tissue models in conjunction with a physiological model, for example, the general kinetic model (GKM), a new DRO can be generated. Furthermore, by incorporating a disease state (e.g., a tumor), the DRO can be made to more realistically represent standard operating conditions for quantitative imaging algorithms. Specifically, such DROs provide a means of assessing algorithm performance across a model parameter space and facilitating investigation of any spatially dependent biases and variances. This talk will provide an overview of the methodology for generating such DROs in addition to illustrating some potential example applications.
Biography: Dr. Bosca is a research associate in Medical Physics at the University of Wisconsin in Madison. He received his master degree in physics from the University of North Texas and his PhD in medical physics from the Graduate School of Biomedical Sciences at The University of Texas Health Science Center in Houston. His research interests include quantitative MR imaging, particularly pharmacokinetic modeling, the development of realistic digital phantoms to aid in assessing and mitigating sources of bias and variance in quantitative algorithms, and the application of multi parametric quantitative MR imaging (e.g., combing quantitative imaging biomarkers from dynamic contrast enhanced, diffusion tensor, dynamic susceptibility contrast MR techniques) for assessing treatment response. In addition, he is keenly interested in the development and validation of freely available, open source, software tools for use in quantitative imaging studies.
Host: Professor Krishna Nayak
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Talyia White
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Chip-Based Stimulated Brillouin Scattering for Low-Power Microwave Photonic Signal Processing Applications
Fri, Mar 18, 2016 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Benjamin J. Eggleton, University of Sydney
Talk Title: Chip-Based Stimulated Brillouin Scattering for Low-Power Microwave Photonic Signal Processing Applications
Abstract: The last few years have seen major progress in harnessing on-chip photon-phonon interactions, leading to a wide range of demonstrations of new functionalities. Utilizing not only the optical response of a nonlinear waveguide - but also hypersound acoustic resonances - enables the realization of microwave devices with unprecedented performance. Here we overview on-chip Stimulated Brillouin scattering (SBS) with special emphasis on reconfigurable and broadband microwave signal processing schemes. We review the different material platforms and structures for on-chip SBS, ranging from chalcogenide rib waveguides to CMOS compatible hybrid silicon/silicon-nitride structures and silicon nanowires. We show that the paradigm shift in SBS research - from long length of fibers to chip scale devices - is now moving towards fully integrated photonic-phononic CMOS chips.
Biography: Professor Benjamin Eggleton is an ARC Laureate Fellow and Professor of Physics at the University of Sydney and Director of the ARC Centre for Ultrahigh bandwidth Devices for Optical Systems (CUDOS). He obtained his PhD degree in Physics from the University of Sydney, in 1996 and then joined Bell Laboratories, Lucent Technologies as a Postdoctoral Member of Staff. In 2000, he was promoted to Director within the Specialty Photonics Division of Bell Laboratories, where he was engaged in forward-looking research supporting Lucent Technologies business in optical fiber devices. He returned to the University of Sydney in 2003 as the founding Director of CUDOS and Professor in the School of Physics.
Professor Eggleton is a Fellow of the Optical Society of America, IEEE Photonic and the Australian Technology, Science and Engineering Academy (ATSE).He was the recipient of the 2011 Eureka Prize for Leadership in Science, the Walter Boas Medal of the Australian Institute of Physics and the OSA's Adolph Lomb Medal. Eggleton has published about 400 journal papers which have been cited >15,000 times with an h-number of > 59 (webofscience). He was President of the Australian Optical Society, is currently Editor-in-Chief for APL Photonics and serves on the Board of Governors for IEEE Photonics.
Host: Alan Willner, x04664, willner@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Gerrielyn Ramos
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Addressing Spectrum Scarcity through Optical Wireless Communications
Mon, Mar 21, 2016 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Mohamed-Slim Alouini, King Abdullah University of Science and Technology
Talk Title: Addressing Spectrum Scarcity through Optical Wireless Communications
Abstract: Rapid increase in the use of wireless services over the last two decades has lead the problem of the radio-frequency (RF) spectrum exhaustion. More specifically, due to this RF spectrum scarcity, additional RF bandwidth allocation, as utilized in the recent past, is not anymore a viable solution to fulfill the demand for more wireless applications and higher data rates. The talk goes first over the potential offered by optical wireless communications to relieve spectrum scarcity. It then summarizes some of the challenges that need to be surpassed before such kind of systems can be massively deployed. Finally the talk offers an overview of some of the recent results for the determination of the capacity of optical wireless channels.
Biography: Mohamed-Slim Alouini (S'94, M'98, SM'03, F'09) was born in Tunis, Tunisia. He received the Ph.D. degree in Electrical Engineering from the California Institute of Technology (Caltech), Pasadena, CA, USA, in 1998. He served as a faculty member in the University of Minnesota, Minneapolis, MN, USA, then in the Texas A&M University at Qatar, Education City, Doha, Qatar before joining King Abdullah University of Science and Technology (KAUST), Thuwal, Makkah Province, Saudi Arabia as a Professor of Electrical Engineering in 2009. His current research interests include the modeling, design, and performance analysis of wireless communication systems.
Host: Andreas Molisch, molisch@usc.edu EEB 530, x04670
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 539
Audiences: Everyone Is Invited
Contact: Gerrielyn Ramos
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
EE 598 Cyber-Physical Systems Seminar Series
Mon, Mar 21, 2016 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Marilyn Wolf, Georgia Institute of Technology
Talk Title: Service-oriented Architectures for Cyber-physical Systems
Abstract: Service-oriented architectures are widely used in information processing and Web technologies to provide scalable access to resources in distributed systems and extensible applications. However, many traditional service-oriented architectures are designed for transaction processing. In contrast, cyber-physical systems used for real-time control require quality-of-service constraints and graceful handling of failures to provide requested services. Our group is developing extended service-oriented models for use in smart energy grids and other applications. We will describe our work in service-oriented architectures, including model-based design and simulation.
Biography: Marilyn Wolf is Rhesa S. "Ray" Farmer Distinguished Chair in Embedded Computing Systems and Georgia Research Alliance Eminent Scholar at the Georgia Institute of Technology. She received her BS, MS, and PhD in electrical engineering from Stanford University in 1980, 1981, and 1984, respectively. She was with AT&T Bell Laboratories from 1984 to 1989. She was on the faculty of Princeton University from 1989 to 2007. Her research interests include cyber-physical systems, embedded computing, embedded video and computer vision, and VLSI systems. She has received the ASEE Terman Award and IEEE Circuits and Systems Society Education Award. She is a Fellow of the IEEE and ACM and an IEEE Computer Society Golden Core member.
Host: Paul Bogdan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Estela Lopez
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
EE-EP Seminar - Dion Khodagholy, Monday, March 21st at 2:00pm in EEB 132
Mon, Mar 21, 2016 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dion Khodagholy, New York University Langone Medical Center
Talk Title: Large-Scale Organic Neural Interface Devices
Abstract: Recording from neural networks at the temporal resolution of action potentials is critical for understanding how information is processed in the brain. We developed an organic, conformable, biocompatible and scalable neural interface electrode and transistor arrays that can record both Local Field Potential (LFP) and extracellular action potentials without penetrating the brain surface. We recorded spiking activity in both rodent experiments and intra-operatively in patients undergoing epilepsy surgery using a large-scale surface probe designed to enable localization of fine LFP activity and the underlying neuronal entrainment. Large-scale, chronically recorded data generated by these devices has broad applicability to the understanding of physiologic and pathologic network activity, control of brain-machine interfaces, and therapeutic closed-loop devices.
Biography: Dion Khodagholy is a fellow at the Simon's Society of Fellows and a postdoctoral research associate in Prof. GyoÌrgy BuzsaÌki's laboratory at New York University Langone Medical Center (NYULMC). He received his Masters degree from University of Birmingham (UK) in Electronic and Communication Engineering. This was followed by a second Masters degree in Microelectronics at Ecole des Mines (France) combined with industry experience at Microelectronic Center of Provence. He attained his Ph.D. degree in Microelectronics at the Department of Bioelectronics (BEL) of Ecole des Mines with Prof. George Malliaras. At BEL, he focused on understanding organic semiconductor device physics and developing organic-based devices to interface with biology. His postdoctoral research at NYULMC is focused on three main domains: (i) design and development of large-scale, organic material-based neural interface devices; (ii) analysis of neural data acquired by these devices to understand large-scale neural network function; (iii) translation of these advancements to neural data acquisition systems in patients with epilepsy. His research explores the interface of electronics and the brain in the context of both applied and discovery sciences, with the ultimate goal of innovating in device engineering and neuroscience methods to improve diagnosis and treatment of neuropsychiatric disease.
Host: EE-Electrophysics
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Network Approaches to Data-Driven Problems: Fundamental Limits, Scalable Algorithms, and Applications
Tue, Mar 22, 2016 @ 02:30 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Soheil Feizi, Massachusetts Institute of Technology
Talk Title: Network Approaches to Data-Driven Problems: Fundamental Limits, Scalable Algorithms, and Applications
Abstract: In large-scale data-driven problems, network modeling provides a unifying framework to succinctly represent data, reveal underlying data structures, and facilitate experiment design. In practice, however, size, uncertainty and complexity of the underlying associations render these applications challenging. In this talk, I will illustrate the use of spectral, combinatorial, and statistical inference techniques in learning the network topology and subsequent network analysis.
First, we introduce Network Maximal Correlation (NMC), a multivariate measure of nonlinear association suitable for large datasets. NMC infers transformations of variables to reveal underlying nonlinear dependencies among them. We characterize NMC using geometric properties of Hilbert spaces and illustrate its application in learning graphical models when variables have unknown nonlinear dependencies. Next, we discuss the problem of network alignment that aims to find a bijective mapping across two graphs so that, if two nodes are connected in one graph, their images are also connected in the other graph. This problem has a broad range of applications for comparative network analysis in systems biology, social sciences and engineering areas. To solve this combinatorial problem, we present a new scalable spectral algorithm, and establish its efficiency, theoretically and experimentally, over several synthetic and real networks.
Biography: Soheil Feizi is a Ph.D. candidate in the Electrical Engineering and Computer Science (EECS) Department at Massachusetts Institute of Technology (MIT), co-supervised by Prof. Muriel Médard and Prof. Manolis Kellis. His research focuses on complex network analysis using tools and concepts from optimization, machine learning, statistical inference and information theory. Previously, he completed a M.Sc. in Electrical Engineering at MIT, where he received the Jacobs Presidential Fellowship and EECS Great Educators Fellowship, as well as an Ernst Guillemin Award for his Master of Science Thesis. He also received the best student award in Electrical Engineering at Sharif University of Technology from where he holds his B.Sc.
Host: Salman Avestimehr
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Suzanne Wong
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Communications, Networks & Systems (CommNetS) Seminar
Wed, Mar 23, 2016 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Farzad Farnoud, Caltech
Talk Title: Stochastic and Information-theoretic Approaches to Analysis of Biological Data
Series: CommNetS
Abstract: The significant growth in the volume and variety of biological data over the past two decades has created plenty of opportunities for data analytics, with essential applications to biology and medicine. In this talk, I will present our work on aspects of analysis and fusion of biological data, leveraging tools from information theory, machine learning, and stochastic modeling. First, I will present an estimation framework for studying the rates of DNA tandem duplication and substitution mutations by analyzing DNA tandem repeat regions. These regions form about 3% of the human genome and are known to cause several diseases. The proposed method, obtained through a stochastic approximation framework, has smaller estimation error compared to previous work and enables the study of various factors affecting mutation rates through the study of a single genome. Second, I will describe HyDRA, a data fusion tool for gene prioritization, which is the task of computationally identifying genes that are most likely to cause a certain disease. HyDRA relies on novel distances between rankings and rank aggregation methods to combine data from various biological datasets. We show that it achieves better accuracy in identifying disease genes while being more scalable compared to the state-of-the-art methods.
Biography: Farzad Farnoud is a postdoctoral scholar at the California Institute of Technology. He received his MS degree in Electrical and Computer Engineering from the University of Toronto in 2008. From the University of Illinois at Urbana-Champaign, he received his MS degree in mathematics and his PhD in Electrical and Computer Engineering in 2012 and 2013, respectively. His research interests include the information-theoretic and probabilistic analysis of genomic evolutionary processes; rank aggregation and gene prioritization; and coding for flash memory and DNA storage. He is the recipient of the 2013 Robert T. Chien Memorial Award from the University of Illinois for demonstrating excellence in research in electrical engineering and the recipient of the 2014 IEEE Data Storage Best Student Paper Award.
Host: Dr. Salman Avestimehr
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Annie Yu
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Efficient Redundancy Techniques to Reduce Delay in Cloud Systems
Thu, Mar 24, 2016 @ 10:30 AM - 11:30 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Gauri Joshi, Massachusetts Institute of Technology
Talk Title: Efficient Redundancy Techniques to Reduce Delay in Cloud Systems
Abstract: Ensuring fast and seamless service to users is critical for today's cloud services. However, guaranteeing fast response can be challenging due to random service delays that are common in today's data centers. In this talk I explore the use the redundancy to combat such service variability. For example, replicating a computing task at multiple servers and then waiting for the earliest copy saves service time. But the redundant tasks can cost more computing resources and also delay subsequent tasks. I present a queuing-theoretic framework to answer fundamental questions such as:
1) How many replicas to launch?
2) Which queues to join?
3) When to issue and cancel the replicas?
This framework reveals surprising regimes where replication reduces both delay as well as resource cost. The task replication idea can also be generalized to analyze latency in content download from erasure coded storage. More broadly, this work lays the theoretical foundation for studying queues with redundancy, uncovering many interesting future directions in cloud infrastructure, crowdsourcing and beyond.
Biography: Gauri Joshi is a Ph.D candidate at MIT EECS where she completed an S.M. in 2012. Her research interests include probabilistic modeling, coding theory and statistical inference. Before coming to MIT, she completed a B.Tech and M. Tech in Electrical Engineering from the Indian Institute of Technology (IIT) Bombay in 2010. She has held summer internships at Google, Bell Labs and Qualcomm. Gauri's awards and honors include the Best Thesis Prize in Computer science at MIT (2012), Institute Gold Medal of IIT Bombay (2010), Claude Shannon Research Assistantship (2015-16), and Schlumberger Faculty for the Future fellowship (2011-2015).
Host: Viktor Prasanna
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Suzanne Wong
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Imaging Seminar - Junjie Yao, Friday, March 25th at 2:00pm in EEB 132
Fri, Mar 25, 2016 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Junjie Yao, Washington University in St. Louis, Missouri
Talk Title: Photoacoustic Imaging beyond Traditional Limits
Abstract: By physically combining electromagnetic and ultrasonic waves, photoacoustic imaging (PAI) has proven powerful for multi-scale anatomical, functional, and molecular imaging. In PAI, a short-pulsed laser beam illuminates the biological tissue to generate a small but rapid temperature rise, which leads to emission of ultrasonic waves due to thermoelastic expansion. The high-frequency ultrasonic waves are detected outside the tissue by an ultrasonic transducer to form an image that maps the original optical energy deposition in the tissue. PAI seamlessly combines the rich optical absorption contrast of biological tissue with the high optically- or acoustically-determined spatial resolutions.
My talk will focus on three recent advances of PAI on exciting new fronts. First, PAI has broken the optical-diffraction limit and achieved super-resolution (~80 nm) imaging by using non-linear photobleaching or photo-switching dynamics, extending its applications into sub-cellular nano-dimensions. Second, by using a novel pulse-width-based single-wavelength method, ultra-fast photoacoustic microscopy has achieved a 1D oxygenation imaging rate of 100 kHz, allowing label-free imaging of mouse brain activity with high spatial-temporal resolution. Third, taking advantage of the newly developed near-infrared non-fluorescent phytochrome BphP1, which can be reversibly switched on and off, PAI has achieved more than 200 times enhancement in detection sensitivity in reporter gene imaging, allowing early-stage cancer imaging at ~10 mm in tissue with a detection sensitivity of ~20 cancer cells.
Biography: Dr. Junjie Yao received his B.E. and M.E. degrees in Biomedical Engineering from Tsinghua University, Beijing, in 2006 and 2008, respectively. He received his Ph.D. degree in Biomedical Engineering at Washington University, St. Louis (WUSTL), in 2013. He is currently a postdoctoral research associate at WUSTL.
Dr. Junjie Yao's research interest is in photoacoustic imaging technologies in life sciences, especially in functional brain imaging and early cancer detection. Dr. Yao has published more than 60 articles in peer-reviewed journals such as Nature Methods, Nature Medicine, PNAS, and PRL. These publications have received more than 1650 world-wide citations in the last five years. He (co-)invented photoacoustic Doppler-bandwidth flowmetry, photoacoustic oxygen metabolic microscopy, photo-imprint super-resolution photoacoustic microscopy, and reversibly-switchable photoacoustic tomography. Dr. Yao's future research will center on developing novel photoacoustic technologies and translating the laboratory imaging advances into diagnostic and therapeutic applications for a broad range of diseases, especially brain disorders and cancers.
Host: EE-Electrophysics
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
The Underpinning of the Industrial Internet of Things
Fri, Mar 25, 2016 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Jan Van Bruaene, VP of Engineering Real-Time Innovations
Talk Title: The Underpinning of the Industrial Internet of Things
Abstract: In this presentation, you will learn about the industrial internet of things and how it differs from the consumer internet of things. We'll also cover why building a connectivity platform for the industrial internet of thing is hard. We'll dig deeper into the underlying technology: Data Distribution Service (DDS). We'll cover data centricity, different communication patterns, and quality of service.
Finally, you will also learn about research and career opportunities at RTI.
Biography: Jan joined RTI in 2006 and has over 19 years of experience in technical and customer-facing leadership roles at companies such as Sun Microsystems and VLSI Technology. He has led professional services, support, and engineering organizations and has experience in middleware, and infrastructure software, operating system s and network chip development.
Jan came to RTI as a senior application engineer and was responsible for developing a new support organization which achieved a record-setting 98 percent customer satisfaction rate. Jan led a team of application services engineers delivering system design and custom implementations using RTI Connext technology and middleware. For the past four years, Jan has managed RTI's R&D organization.
Jan graduated with a MS equivalent degree in Electronics, Digital Communications (Summa Cum Laude) from KIHK in Geel, Belgium.
Host: Bhaskar Krishnamachari
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Shane Goodoff
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
EE 598 Cyber-Physical Systems Seminar Series
Mon, Mar 28, 2016 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Krishnendu Chakrabarty, Professor, Duke University
Talk Title: Digital Microfluidic Biochips: From Manipulating Droplets to A Cyberphysical System for Quantitative Gene-Expression Analysis
Abstract: Advances in microfluidics have led to the emergence of biochips for automating laboratory procedures in molecular biology. These devices enable the precise control of nanoliter volumes of biochemical samples and reagents. As a result, non-traditional biomedical applications and markets (e.g., high-throughout DNA sequencing, portable and point-of-care clinical diagnostics, protein crystallization for drug discovery), and fundamentally new uses are opening up for ICs and systems. This lecture will first introduce electrowetting-based digital microfludic biochips and provide an overview of market drivers such as immunoassays and DNA sequencing. The audience will next learn about design automation and reconfiguration aspects of microfluidic biochips. Synthesis tools will be described to map assay protocols from the lab bench to a droplet-based microfluidic platform and generate an optimized schedule of bioassay operations, the binding of assay operations to functional units, and the layout and droplet-flow paths for the biochip. The role of the digital microfluidic platform as a "programmable and reconfigurable processor" for biochemical applications will be highlighted. The speaker will describe dynamic adaptation of bioassays through cyberphysical system integration and sensor-driven on-chip error recovery.
Finally, the speaker will highlight recent advances in utilizing cyberphysical integration for quantitative gene-expression analysis. This framework is based on a real-time resource-allocation algorithm that responds promptly to decisions about the protocol flow received from a firmware layer. Results will be presented on how this adaptive framework efficiently utilizes on-chip resources to reduce time-to-result without sacrificing the chip's lifetime.
Biography: Krishnendu Chakrabarty received the B. Tech. degree from the Indian Institute of Technology, Kharagpur, in 1990, and the M.S.E. and Ph.D. degrees from the University of Michigan, Ann Arbor, in 1992 and 1995, respectively. He is now the William H. Younger Distinguished Professor of Engineering in the Department of Electrical and Computer Engineering and Professor of Computer Science at Duke University. He also serves as Director of Graduate Studies for Electrical and Computer Engineering. Prof. Chakrabarty is a recipient of the National Science Foundation Early Faculty (CAREER) award, the Office of Naval Research Young Investigator award, the Humboldt Research Award from the Alexander von Humboldt Foundation, Germany, the IEEE Transactions on CAD Donald O. Pederson Best Paper award (2015), and 11 best paper awards at major IEEE conferences. He is also a recipient of the IEEE Computer Society Technical Achievement Award (2015) and the Distinguished Alumnus Award from the Indian Institute of Technology, Kharagpur (2014). He is a Research Ambassador of the University of Bremen, Germany. He has been a Visiting Professor at University of Tokyo, Japan (2013), a Chair Professor at Tsinghua University, China (2009-2014), and a Visiting Chair Professor at National Cheng Kung University, Taiwan (2012-2013).
Prof. Chakrabarty's current research projects include: testing and design-for-testability of integrated circuits; digital microfluidics, biochips, and cyberphysical systems; optimization of enterprise systems and smart manufacturing. He is a Fellow of ACM, a Fellow of IEEE, and a Golden Core Member of the IEEE Computer Society. He holds seven US patents, with several patents pending. He was a 2009 Invitational Fellow of the Japan Society for the Promotion of Science (JSPS). He is a recipient of the 2008 Duke University Graduate School Dean's Award for excellence in mentoring, and the 2010 Capers and Marion McDonald Award for Excellence in Mentoring and Advising, Pratt School of Engineering, Duke University. He served as a Distinguished Visitor of the IEEE Computer Society during 2005-2007 and 2010-2012, and as a Distinguished Lecturer of the IEEE Circuits and Systems Society during 2006-2007 and 2012-2013. Currently he serves as an ACM Distinguished Speaker.
Prof. Chakrabarty served as Editor-in-Chief of IEEE Design & Test of Computers (2010-2012) and ACM Journal on Emerging Technologies in Computing Systems (2010-2015). Currently he serves as the Editor-in-Chief of IEEE Transactions on VLSI Systems. He is also an Associate Editor of IEEE Transactions on Computers, IEEE Transactions on Biomedical Circuits and Systems, IEEE Transactions on Multiscale Computing Systems, and ACM Transactions on Design Automation of Electronic Systems.
Host: Paul Bogdan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Estela Lopez
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
EE-EP Seminar - Renjie Zhou, Tuesday, March 29th at 2:00pm in EEB 132
Tue, Mar 29, 2016 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Renjie Zhou, George R. Harrison Spectroscopy Laboratory at MIT
Talk Title: Quantitative Phase Microscopy: a label-free platform for material metrology and biological imaging
Abstract: Advances in imaging sensors and computer chips have enabled us to record holograms on cameras and reconstruct objects information with high fidelity and fast speed. The marriage of digital holography and optical microscopy gave birth to quantitative phase imaging (QPI). QPI precisely maps the amplitude and phase information associated with the electromagnetic field scattered by an object. Recent efforts have pushed QPI instruments to achieve sensitivity better than 10-3, corresponding to less than 1 nm surface height changes, or conversely 10-4 refractive index variations in transparent biological structures. Importantly, QPI is a label-free method, without using fluorescence markers, which has opened many noninvasive imaging applications.
This talk will focus on the instrumentation and image formation of novel QPI systems and highlight their applications in two important domains, namely material metrology and biological imaging. First, I will outline the QPI potential in material characterization and wafer defect inspection. In particular, I will show our wafer metrology instrument development and its capability for densely patterned semiconductor wafer defect inspection, detecting deep sub-wavelength patterning defects in 22nm and 9nm node silicon wafers. After that, I will move my focal point to the development of QPI-based biological imaging techniques. Especially, I will talk about solving the inverse scattering problem for determining the structure of cells in 3D, which led to the invention of white-light diffraction tomography (WDT). WDT is compatible with most exiting phase contrast microscopes, thus, it can potentially complement fluorescence imaging by providing additional biophysical markers. At the end, I will discuss some potential research areas along the QPI direction, including neuron activity imaging, stem cell identification, and cell mechanics characterization.
Biography: Renjie Zhou is a postdoctoral associate at George R. Harrison Spectroscopy Laboratory at MIT, where his research centers on developing ultra-sensitive interferometric microscopy systems and high throughput 3D imaging methods for biomedical applications. Dr. Zhou received PhD in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign (UIUC) in 2014. His dissertation focused on developing wafer defect inspection instruments and solving 3D inverse scattering problems for cell imaging. Dr. Zhou has co-authored over 40 peer-reviewed journal and conference papers and filed 4 US patent applications. He has received a number of research awards including the Arnold Beckman Fellowship from the Beckman Foundation, Scholarship in Optics & Photonics and Newport Spectra - Physics Research Excellence Travel Grant from SPIE; Jean Bennett Memorial Student Travel Grant finalist from OSA; P. D. Coleman Outstanding Research Award, Yuen T. Lo Outstanding Graduate Research Award, and Sundaram Seshu International Student Fellowship from UIUC. In addition, Dr. Zhou's research work was featured in Nature, NSF, OSA, and SPIE news.
Host: EE-Electrophysics
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Continuous Mobile Vision Systems for Efficiency and Privacy
Wed, Mar 30, 2016 @ 10:30 AM - 11:30 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Robert LiKamWa, Rice University
Talk Title: Continuous Mobile Vision Systems for Efficiency and Privacy
Abstract: The future of computing is in allowing our devices to see what we see. I envision wearable systems that continuously interpret vision data for real-time analytics. Today's system software and imaging hardware are ill-suited for this goal of "continuous mobile vision." Current systems, highly optimized for photography, fail to achieve sufficient energy efficiency or privacy preservation. This talk provides a rethinking of the vision system stack that includes application frameworks, operating system and sensor hardware to improve efficiency by two orders of magnitude. This cross layer rethinking contributes: (1) a split-process application framework that eliminates redundancy in data movement and processing across multiple concurrent applications, (2) operating system optimizations for energy proportional image capture, and (3) a mixed-signal image sensor architecture that processes data in the analog domain to eliminate the efficiency bottleneck of analog-digital conversion. The talk will briefly share future plans to further continuous mobile vision by exploiting the hardware/software boundary for improved energy efficiency and effective privacy preservation, opening the door to integrate our devices with our real world-environments and ultimately, our own lives.
Biography: Robert LiKamWa is a final-year PhD Student at Rice University. As a Mobile Systems researcher, he operates at the intersection of Operating Systems and Computer Architecture. His dissertation research focuses on system support for continuous mobile vision. He has interned and collaborated with Microsoft Research and Samsung Mobile Processor Innovation Lab on various projects related to vision systems. LiKamWa is supported by a Texas Instruments Graduate Fellowship, and received best paper awards from ACM MobiSys 2013 and PhoneSense 2011.
Host: Konstantinos Psounis
Location: 248
Audiences: Everyone Is Invited
Contact: Suzanne Wong
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Seminar-Algorithms for detecting atypical language use in autism spectrum disorders
Thu, Mar 31, 2016 @ 10:00 AM - 11:20 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Jan van Santen, Center for Spoken Language Understanding, Institute on Development and Disability, Oregon Health & Science University
Talk Title: Algorithms for detecting atypical language use in autism spectrum disorders
Abstract: The DSM-5 lists repetitiveness and impaired reciprocal social interaction as core symptoms of autism spectrum disorder (ASD), but does not list language impairment. Yet, language use is often atypical in ASD, being a natural modality for core symptoms to manifest. Standard language measures are not optimal for capturing these characteristics because they are too structured: Analysis of natural language samples is needed. However, such analysis is time consuming and inexact when conducted manually. Computational methods are needed.
We developed and applied algorithms to transcripts of Autism Diagnostic Observation Schedule (ADOS) sessions with children ages 4-8 with high-functioning ASD, Specific Language Impairment (SLI), or Typical Development (TD). The ASD group was divided into children with SLI (ALI) and without (ALN). Results showed ASD-specific atypicalities in verbatim and topical repetitiveness, discourse marker use, type of disfluencies, and other features of language use. These results attest to the feasibility of computing ASD-specific characteristics from natural language samples, tapping into multiple aspects of core ASD symptoms. Their usefulness is demonstrated by the intricate pattern of differences and similarities between the ASD and SLI groups and the ALI and ALN groups.
Biography: Jan van Santen obtained his PhD in Mathematical Psychology at the University of Michigan in 1979. He worked initially on visual perception and image processing at New York University and Bell Labs, and then switched to speech technology in 1985. He developed the prosody generation components of the Bell Labs text-to-speech system. In 2000 he became the Director of the Center for Spoken Language Understanding, now part of the Oregon Health & Science University. Here, he became one of the pioneers of a growing new field: the application of Natural Language Processing algorithms to neurological and neurodevelopmental disorders for diagnostics, remediation, and assistive communication, with special emphasis on autism spectrum disorders. In his spare time, he runs a startup, BioSpeech, that works on algorithms for processing biological sounds, including not only speech but also snoring and rodent calls.
He has written over 100 peer-reviewed papers, was an editor of Speech Communication and of the Journal of Mathematical Psychology, was the editor of a book, Progress in Speech Synthesis, and has seven patents.
Host: Shrikanth Narayanan & Daniel Bone
Location: Ronald Tutor Hall of Engineering (RTH) - 211
Audiences: Everyone Is Invited
Contact: Tanya Acevedo-Lam/EE-Systems
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Cyber-Physical System Design Using Contracts
Thu, Mar 31, 2016 @ 10:00 AM - 11:30 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Pierluigi Nuzzo, University of California, Berkeley
Talk Title: Cyber-Physical System Design Using Contracts
Abstract: The realization of complex cyber-physical systems is creating design and verification challenges that will soon become insurmountable with today's engineering practices. While model-based design tools are already facilitating several design tasks, harnessing the complexity of the Internet-of-Things scenario is only deemed possible within a unifying methodology. This methodology should help interconnect different tools, possibly operating on different system representations, to enable scalable design space exploration and early detection of requirement inconsistencies.
In this talk, I show how a contract-based approach provides a formal foundation for a compositional and hierarchical methodology for cyber-physical system design, which can address the above challenges, and encompass both horizontal and vertical integration steps. I use assume guarantee contracts and their algebra (e.g. composition, conjunction, and refinement) to support the entire design process and enable concurrent development of system architectures and control algorithms. In the methodology, the design is carried out as a sequence of refinement steps from a high-level specification to an implementation built out of a library of components at the lower level. Top-level system requirements are represented as contracts, by leveraging a set of formal languages, including mixed integer-linear constraints and temporal logic. Contracts are then refined by combining synthesis and optimization-based methods. I propose a set of optimization-based algorithms for efficient selection of cost-effective architectures under safety, reliability, and performance constraints over a large, mixed discrete-continuous design space. I demonstrate the effectiveness of the approach on industrial design examples, including aircraft electric power distribution and environmental control systems, showing, for instance, that optimal selection of industrial-scale power system architectures can be performed in a few minutes. Finally, I conclude by presenting future research directions towards a full-fledged integrated framework for system design.
Biography: Pierluigi Nuzzo is a Postdoctoral Scholar at the Department of Electrical Engineering and Computer Sciences of the University of California, Berkeley. He received the Ph.D. in Electrical Engineering and Computer Sciences from the University of California at Berkeley in 2015. He also holds the Laurea (M.Sc.) degree in Electrical Engineering (summa cum laude) from the University of Pisa and the Sant'Anna School of Advanced Studies, Pisa, Italy. Before joining U.C. Berkeley, he was a Researcher at IMEC, Leuven, Belgium, and the University of Pisa, working on the design of energy-efficient A/D converters, frequency synthesizers for reconfigurable radio, and design methodologies for mixed-signal integrated circuits. His research interests include: methodologies and tools for cyber-physical system and mixed-signal system design; contracts, interfaces, and compositional methods for embedded system design; energy-efficient analog and mixed-signal circuit design. Pierluigi received First Place in the operational category and Best Overall Submission in the 2006 DAC/ISSCC Design Competition, a Marie Curie Fellowship from the European Union in 2006, the University of California at Berkeley EECS departmental fellowship in 2008, the U.C. Berkeley Outstanding Graduate Student Instructor Award in 2013, and the IBM Ph.D. Fellowship in 2012 and 2014.
Host: Dr. Massoud Pedram
Location: 248
Audiences: Everyone Is Invited
Contact: Suzanne Wong
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor.
