SUNMONTUEWEDTHUFRISAT
Conferences, Lectures, & Seminars
Events for April
-
Center for Cyber-Physical Systems and Internet of Things and Ming Hsieh Institute for Electrical Engineering Joint Seminar Series on Cyber-Physical Systems
Mon, Apr 03, 2017 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Oleg Sokolsky, Research Professor, University of Pennsylvania
Talk Title: Behavior Modeling in Patient-in-the-Loop Medical CPS
Abstract: Human-in-the-loop cyber-physical systems (CPS) is an active area of research. As the level of autonomy in systems we use every day is rapidly increasing, the problems of human-automation interaction and of trust in technology are becoming more important. In medical CPS, interactions between the human and technology happen both through behavior as well as through patient physiology. This talk motivates the need for modeling and analysis techniques that take both behavioral and physiological interactions into consideration. We present a case study of diabetic patients interacting with smart insulin pumps and consider how behavioral modeling and analysis can impact treatment outcomes.
Biography: Oleg Sokolsky is a Research Professor of Computer and Information Science at PRECISE Center, University of Pennsylvania. His research interests include applications of formal methods and runtime verification to the design and analysis. He received a Ph.D. in Computer Science from State University of New York at Stony Brook.
Host: Paul Bogdan and Chao Wang
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
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. -
Matthew Gilbert, Nano Science & Technology Seminar Series, Tuesday, April 4 at 2:00pm in EEB 248
Tue, Apr 04, 2017 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Matthew J. Gilbert, University of Illinois Urbana-Champaign
Talk Title: Topological Energy Transduction
Abstract: Within the CMOS architecture, the interconnected devices may either be categorized as an "active" device, which produces energy in the form of a current or a voltage, or a "passive" device, which stores or maintains energy in the form of a current or voltage. The societal demand for smaller sized electronic devices, such as computers and cellular phones, with improved functionality has forced not only the sizes of the constituent components of CMOS information processing technology to rapidly shrink, but for the operational frequencies to increase. While it has been possible to reduce the size of active CMOS devices, passive devices have not seen the same reduction in size. Of the passive devices (e.g. resistors, capacitors and inductors) used in CMOS technologies, the circuit element that consumes the most area on a circuit board while simultaneously finding the least success in miniaturization is the inductor. In this talk, we will present a novel method for energy transduction that utilizes the interplay between magnetism and topology on the surface of a newly discovered materials, referred to as time-reversal invariant topological insulators, to create a paradigmatically different inductor. Using a novel self-consistent simulation that couples AC non-equilibrium Green functions to fully electrodynamic solutions of Maxwell's equations, we demonstrate excellent inductance densities up to terahertz frequencies thereby providing a potential solution to an eminent grand challenge.
Biography: Matthew J. Gilbert is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign (UIUC). He is affiliated with the Micro and Nanotechnology Laboratory, the Department of Physics and the Institute for Condensed Matter Theory at UIUC. His research broadly focuses on theoretically elucidating new phenomena in emergent nanoscale systems with the goal of developing new types of nanoelectronic and nanophotonic devices and functionality for next-generation information processing systems. The majority of his current work revolves around understanding the properties of topological materials, including insulators, semimetals and superconductors, with the goal of understanding their potential role in the post-CMOS device landscape. This research also includes examinations into the appearance and stability of unconventional superconductivity and non-Abelian anyons, such as Majorana and parafermions, in topological systems for the purposes of topological quantum computation. His emerging research interests include: the role of interactions in the classification and properties of topological systems, dissipation and relaxation in non-equilibrium materials and systems, transport properties and phenomena in 2D materials particularly those under strain, energy harvesting using topological materials, and designer layered quantum materials. He has authored more than 70-refereed publications, and has given presentations at over 50 international conferences.
Host: Wang, Zhou, Cronin, Wu - MHI
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
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. -
Matthew Gilbert - Nano Science & Technology Seminar Series, Wednesday, April 5th at 2:00pm in KAP 209
Wed, Apr 05, 2017 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Matthew J. Gilbert, University of Illinois Urbana-Champaign
Talk Title: Unconventional Superconductivity in Topological Heterostructures
Abstract: The search for materials and systems that exhibit unconventional superconductivity, or superconductivity beyond the canonical s-wave pairing as predicted in BCS theory, is one of the most active areas within condensed matter physics. This effort has been reinvigorated by the interesting properties inherent to a new class of materials that possess topological phases. A topological phase is unique in that it does not break any of the underlying symmetries of the system and cannot be described by a local order parameter. In other words, the inherent properties of the system cannot be changed by adiabatic shifts in materials parameters unless the system passes a quantum critical point associated with a phase transition. More recently, this search has taken on additional significance due to the fact that systems that possess unconventional superconductivity may enable a new type of fault tolerant quantum information processing that may significantly increase computing power when compared to traditional information processing. In this talk, I will discuss the appearance and signatures of unconventional superconductivity and review some of the most prominent systems that have been predicted to exhibit unconventional superconductivity. In particular, I will focus on heterostructures containing s-wave superconductors and proximity-coupled 3D time-reversal invariant topological insulators. I will explain some of the experimentally relevant conditions that must be satisfied in order to observe the features of unconventional superconductivity and conclude by examining the potential for finding unconventional superconductivity in emergent topological materials such as semimetals and crystalline insulators.
Biography: Matthew J. Gilbert is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign (UIUC). He is affiliated with the Micro and Nanotechnology Laboratory, the Department of Physics and the Institute for Condensed Matter Theory at UIUC. His research broadly focuses on theoretically elucidating new phenomena in emergent nanoscale systems with the goal of developing new types of nanoelectronic and nanophotonic devices and functionality for next-generation information processing systems. The majority of his current work revolves around understanding the properties of topological materials, including insulators, semimetals and superconductors, with the goal of understanding their potential role in the post-CMOS device landscape. This research also includes examinations into the appearance and stability of unconventional superconductivity and non-Abelian anyons, such as Majorana and parafermions, in topological systems for the purposes of topological quantum computation. His emerging research interests include: the role of interactions in the classification and properties of topological systems, dissipation and relaxation in non-equilibrium materials and systems, transport properties and phenomena in 2D materials particularly those under strain, energy harvesting using topological materials, and designer layered quantum materials. He has authored more than 70-refereed publications, and has given presentations at over 50 international conferences.
Host: Wang, Zhou, Cronin, Wu - MHI
Location: Kaprielian Hall (KAP) - 209
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. -
MHI CommNetS seminar
Wed, Apr 05, 2017 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Hamidreza Tavafoghi, University of Michigan
Talk Title: Dynamic Market Mechanisms for Wind Energy
Series: CommNetS
Abstract: We investigate the problem of market mechanism design for wind energy integration into the power grid. We show that the current static two-settlement market structure is not efficient for the integration of wind energy, and does not provide appropriate information for scheduling of flexible loads/reserves. We consider a dynamic two-step model with strategic seller(s) with wind generation and one buyer, who trade energy through a mechanism determined by a designer (ISO). The seller has private information about his technology and wind condition, which he learns dynamically over time. We consider the existing (static) forward and real-time mechanisms that take place at times T = 1 and T = 2, respectively. We propose a dynamic mechanism that provides a coupling between the outcomes of the forward and real-time markets, and show that the dynamic mechanism outperforms the forward and real-time mechanisms for a general objective of the designer. We demonstrate that the advantages of our proposed dynamic mechanism come from the designer's ability to price discriminate and the seller's exposure to penalty risk. Moreover, our proposed mechanism reveals (probabilistic) information about wind generation in advance so as to schedule flexible loads/reserves efficiently. We further analyze variants of the dynamic mechanism that guarantee no penalty risk for sellers, and/or monitor the wind condition.
Biography: Hamidreza Tavafoghi is a Ph.D. candidate in the Electrical Engineering and Computer Science department at the University of Michigan working with Prof. Demosthenis Teneketzis, where he also pursues a M.A. in Economics. His research interests lie in stochastic control, game theory, mechanism design, and strategic learning. Currently, he is working on the design and analysis of informational and monetary incentive mechanisms for cyber-physical systems with applications to power systems, transportation networks, and security. Hamidreza received his B.Sc. in Electrical Engineering from Sharif University of Technology, Tehran, Iran, 2011, and his M.Sc. in Electrical Engineering: Systems from the University of Michigan, 2013. He was awarded the Dow Sustainability Fellowship in 2015. He is a Silver medalist of 37th International Physics Olympiad, Singapore, 2006, and a Gold medalist of 18th National Physics Olympiad, Iran, 2005.
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. -
Ming Hsieh Institute Seminar Series on Integrated Systems
Fri, Apr 07, 2017 @ 02:30 PM - 04:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Hua Wang, Assistant Professor, Georgia Institute of Technology
Talk Title: Pushing the Envelope of RF mmWave Power Generation by Relearning Ohms Law
Host: Profs. Hossein Hashemi, Mike Chen, Dina El-Damak, and Mahta Moghaddam
More Information: MHI Seminar Series IS - Hua Wang.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Jenny Lin
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. -
Emerging Trends Seminar Series
Mon, Apr 10, 2017 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: C.C. Jay Kuo, Dean's Professor of Electrical Engineering, Ming Hsieh Department of Electrical Engineering
Talk Title: CNN as Guided Multi-layer RECOS Transform
Series: Emerging Trends
Abstract: There is a resurging interest in developing a neural network based solution to supervised machine learning in the last 5 years. In this talk, I will provide a theoretical foundation to the working principle of the convolutional neural network (CNN) from a signal processing viewpoint. To begin with, the RECOS transform is introduced as a basic building block for CNNs.
The term RECOS is an acronym for REctified-COrrelations on a Sphere. It consists of two main concepts: data clustering on a sphere and rectification. Then, a CNN is interpreted as a network that implements the guided multilayer RECOS transform. Along this line, we first compare the traditional single-layer and modern multilayer signal analysis approaches. Then, we discuss how guidance is provided by data labels through back propagation in the training with an attempt to offer a smooth transition from weakly to heavily supervised learning. Finally, we show that a trained network can be greatly simplified in the testing stage, which demands only one bit representation for both filter weights and inputs. Several future research directions are pointed out at the end.
Biography: Dr. C.C. Jay Kuo received his Ph.D. degree from the Massachusetts Institute of Technology in 1987. He is now with the University of Southern California (USC) as Director of the Media Communications Laboratory and Dean's Professor in Electrical Engineering, Systems. His research interests are in the areas of digital media processing, compression, communication and networking technologies. Dr. Kuo was the Editor in Chief for the IEEE Trans. on Information Forensics and Security from 2012 through 2014. He was the Editor in Chief for the Journal of Visual Communication and Image Representation from 1997 through 2011, and served as Editor for 10 other international journals.
Dr. Kuo received the 1992 National Science Foundation Young Investigator (NYI) Award, the 1993 National Science Foundation Presidential Faculty Fellow (PFF) Award, the 2010 Electronic Imaging Scientist of the Year Award, the 2010-11 Fulbright-Nokia Distinguished Chair in Information and Communications Technologies, the 2011 Pan Wen Yuan Outstanding Research Award, the 2014 USC Northrop Grumman Excellence in Teaching Award, the 2016 USC Associates Award for Excellence in Teaching, the 2016 IEEE Computer Society Taylor L. Booth Education Award, the 2016 IEEE Circuits and Systems Society John Choma Education Award, the 2016 IS&T Raymond C. Bowman Award, and the 2017 IEEE Leon K. Kirchmayer Graduate Teaching Award. Dr. Kuo is a Fellow of AAAS, IEEE and SPIE. He has guided 140 students to their Ph.D. degrees and supervised 25 postdoctoral research fellows. Dr. Kuo is a co author of about 250 journal papers, 900 conference papers, 14 books and 30 patents.
Host: Ming Hsieh Institute
More Info: https://www.facebook.com/events/1444859602200671/
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Cathy Huang
Event Link: https://www.facebook.com/events/1444859602200671/
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. -
Center for Cyber-Physical Systems and Internet of Things and Ming Hsieh Institute for Electrical Engineering Joint Seminar Series on Cyber-Physical Systems
Mon, Apr 10, 2017 @ 03:00 PM - 04:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Natalie Cheung , Intel
Talk Title: Utilizing Drones to Create a New Nighttime Entertainment
Abstract: Come learn how Intel is utilizing drones in a different way -“ to light up the sky in a choreographed aerial performance with the Intel Drone Light Show. You'll learn about the Intel Shooting Star Drone, the technology behind the show, and more.
Biography: Natalie Cheung is the General Manager for the Drone Light Show in the UAV Group at Intel Corporation. She is responsible for establishing the drone light show business and growing the new segment. Cheung has led drone light show collaborations with customers that created activations across the globe - from the US, Germany, Mexico, Australia, and more.
Prior to her current role, Cheung was the Drone Marketing Director. She was responsible for product launches, conferences and events, and building awareness within the drone segment. Cheung has also served as Drone Product Manager, Research Analyst for Intel CEO Brian Krzanich. Cheung joined Intel in 2011. She earned a bachelor's and master's degree in electrical engineering and computer science from Massachusetts Institute of Technology.
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. -
MHI CommNetS Seminar
Wed, Apr 12, 2017 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Ian M. Mitchell, University of British Columbia
Talk Title: Using model checking verifications online: Handling runtime state uncertainty, human-in-the-loop shared control and sampled data feedback
Series: CommNetS
Abstract: Recent advances in model checking algorithms for continuous state systems allow us to demonstrate the existence of safe control policies robust to model error for cyber-physical systems (CPS) of practical interest, such as shared control drones or wheelchairs, or automated delivery of anesthesia. However, these verification results are only relevant if we can implement those policies. In this talk I will discuss investigations into three challenges that arise when it comes time to synthesize a feedback control signal that will keep the system safe: Online state uncertainty, human-in-the-loop shared control for older adults with cognitive impairment, and the sampled data nature of that feedback control in typical cyber-physical systems.
Biography: Ian M. Mitchell completed his doctoral work in engineering at Stanford University in 2002, spent a year as a postdoctoral researcher at the University of California at Berkeley, and is now an Associate Professor of Computer Science at the University of British Columbia. He is the author of the Toolbox of Level Set Methods, the first publicly available high accuracy implementation of solvers for dynamic implicit surfaces and the time dependent Hamilton-Jacobi equation that works in arbitrary dimension. His research interests include development of algorithms and software for nonlinear differential equations, formal verification, control and planning in cyber-physical and robotic systems, assistive technology and reproducible research.
Host: Prof. Insoon Yang
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. -
Jelena Vuckovic - Munushian Seminar, Friday, April 14th at 2:00pm in EEB 132
Fri, Apr 14, 2017 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Jelena Vuckovic, Stanford University
Talk Title: Quantum Nanophotonics
Abstract: Nanophotonic structures that localize photons in sub-wavelength volumes are possible today thanks to modern nanofabrication and optical design techniques. Such structures enable studies of new regimes of light-matter interaction, quantum and nonlinear optics, and new applications in computing, communications, and sensing. While the traditional quantum nanophotonics platform is based on quantum dots inside photonic crystal cavities, recently a lot of progress has been made on systems consisting of color centers in diamond and silicon carbide, which could potentially bring these experiments to room temperature and facilitate scaling to large networks of resonators and emitters. Moreover, the use of inverse nanophotonic design methods, that can efficiently perform physics-guided search through the full parameter space, leads to optical devices with properties superior to state of the art, including smaller footprints, better field localization, and novel functionalities.
Biography: Jelena Vuckovic (PhD Caltech 2002) has been a faculty at Stanford since 2003, where she is currently a Professor of Electrical Engineering and by courtesy of Applied Physics, and where she leads the Nanoscale and Quantum Photonics Lab. She has also held visiting positions at the Humboldt University in Berlin, Germany, and the Technical University in Munich, Germany. Vuckovic is a recipient of numerous awards, including the Humboldt Prize, the Hans Fischer Senior Fellowship, and the Presidential Early Career Award for Scientists and Engineers (PECASE). She is a Fellow of the American Physical Society (APS) and of the Optical Society of America (OSA), and a member of the scientific advisory board of the Max Planck Institute for Quantum Optics (MPQ) in Munich, Germany.
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. -
Ming Hsieh Institute Seminar Series on Integrated Systems
Fri, Apr 21, 2017 @ 02:00 PM - 04:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Aaron Buchwald, Senior Technical Director at InPhi Corporation
Talk Title: Challenges of Time-Interleaved ADCs
Host: Profs. Hossein Hashemi, Mike Chen, Dina El-Damak, and Mahta Moghaddam
More Information: MHI Seminar Series IS - Aaron Buchwald.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Jenny Lin
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. -
Center for Cyber-Physical Systems and Internet of Things and Ming Hsieh Institute for Electrical Engineering Joint Seminar Series on Cyber-Physical Systems
Mon, Apr 24, 2017 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dennice F. Gayme, Assistant Professor, Johns Hopkins University
Talk Title: Quantifying efficiency and robustness in large-scale networks
Abstract: Dynamical systems coupled over graphs arise in a number of applications from power grids to vehicle networks. These systems are most often characterized in terms of their stability. However, the performance of these networks is also of great importance as it often corresponds to system efficiency and robustness. In this talk, we discuss a broad class of performance measures for first and second order systems whose outputs are defined so that particular performance metrics can be quantified through the input-output H2 norm of the system. We first present results for systems with the same physical interconnection and communication graph structures. We discuss the effect of graph size and interconnection structure for two applications; characterizing transient real power losses in power grids and evaluating long range disorder in vehicular platoons with both relative and absolute velocity feedback. We then extend our results to vehicular networks with arbitrary physical arrangements and communication structures to demonstrate that our proposed suite of performance measures can be adapted to determine the minimum disturbance energy that is required to cause a collision between any two vehicles. Finally, we further explore the effect of graph structure by considering systems with directed communication graphs.
Biography: Dennice F. Gayme is an Assistant Professor and the Carol Croft Linde Faculty Scholar in Mechanical Engineering at the Johns Hopkins University. She earned her B. Eng. & Society from McMaster University in 1997 and an M.S. from the University of California at Berkeley in 1998, both in Mechanical Engineering. She received her Ph.D. in Control and Dynamical Systems in 2010 from the California Institute of Technology, where she was a recipient of the P.E.O. scholar award in 2007 and the James Irvine Foundation Graduate Fellowship in 2003. Her research interests are in modeling, analysis and control for spatially distributed and large-scale networked systems in applications such as wall-bounded turbulent flows, wind farms, power grids and vehicular networks. She was a recipient of the JHU Catalyst Award in 2015, a 2017 ONR Young Investigator award, and an NSF CAREER award in 2017.
Host: Paul Bogdan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
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. -
CommNetS seminar
Tue, Apr 25, 2017 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Christian Grussler, Lund University
Talk Title: Low-Rank Inducing Norms with Optimality Interpretations
Series: CommNetS
Abstract: This talk is on optimization problems which are convex apart from a sparsity/rank constraint. These problems are often found in the context of compressed sensing, linear regression, matrix completion, low-rank approximation and many more. Today, one of the most widely used methods for solving these problems is so-called nuclear norm regularization. Despite the nice probabilistic guarantees of this method, this approach often fails for problems with structural constraints.
In this talk, we will present an alternative by introducing the family of so-called low-rank inducing norms as convexifiers. Each norm is the convex envelope of a unitarily invariant norm plus a rank constraint. Therefore, they have several interesting properties, which will be discussed throughout the talk. They:
i) Give a simple deterministic test if the solution to the convexified problem is a solution to a specific non-convex problem.
ii) Often finds solutions where the nuclear norm fails to give low-rank solutions.
iii) Allow us to analyze the convergence of non-convex proximal splitting algorithms with convex analysis tools.
iv) Provide a more efficient regularization than the traditional scalar multiplication of the nuclear norm.
v) Leads to a different interpretation of the nuclear norm than the one that is traditionally presented.
vi) In particular, all the results can be generalized to so-called atomic norms.
Biography: Christian Grussler is a postdoc at the Department of Automatic Control at Lund University, Sweden. His current research interests include positive systems, model reduction, system identification and low-rank/sparse optimization. He received a Dipl.-Math. techn. degree (Industrial Mathematics) from TU Kaiserslautern, Germany and an M.Sc. degree (Engineering Mathematics) from Lund University in 2011. In 2017, he received a Ph.D. degree from Lund University under the guidance of Anders Rantzer and Pontus Giselsson.
Host: Prof. Mihailo Jovanovic
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
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 Emerging Trends Seminar Series
Wed, Apr 26, 2017 @ 10:00 AM - 11:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Kai Hwang, Professor, Ming Hsieh Department of Electrical Engineering
Talk Title: Big-Data Analytics for Cloud Computing in Cognitive Applications
Series: Emerging Trends
Abstract: In this talk, Dr. Hwang will address the effective use of big-data analytics on smart clouds, social networks, intelligent robots, and IoT platforms. He will assess machine/deep learning models and available software tools to advance the cognitive service industry represented by Google, Microsoft, Apple, Facebook, Baidu, IBM, Huawei, etc. The ultimate goal is to achieve enhanced agility, mobility, security, and scalability of public clouds, IoT platforms, and social-media networks.
His talk will assess current AI programs and brain projects pursued by high-tech companies, including Google X-Lab, TensorFlow, DeepMind AlphaGo, Nvidia Digits 5 for using GPU in deep learning, IBM neuromorphic computer, and CAS/ICT Camericon project, etc. Some hidden R/D opportunities are revealed for building smart machinesï¼delivery drones, self-driving cars, blockchains, AR/VR gears, etc. Extended cognitive applications will be discussed for 5G health-care, desease detection, emotion control, and social media community services.
Biography: Kai Hwang is a Professor of EE/CS at the Univ. of Southern California. He received the Ph.D. from UC Berkeley. He has published extensively in computer architecture, parallel processing, cloud computing, and network security. His latest two books are entitled: Cloud Computing for Machine Learning and Cognitive Applications (The MIT Press, April 2017) and Big Data Analytics for Cloud/IoT and Cognitive Computing (Wiley, U.K, May 2017).
An IEEE Life Fellow, he received the very-first CFC Outstanding Achievement Award in 2004 and the Lifetime Achievement Award from IEEE Cloud2012 for his pioneering work in parallel computing and distributed systems. Four of his graduated Ph.D. students were elected as IEEE Fellows and one an IBM Fellow. He has delivered four dozens of keynote or distinguished lectures in international Conferences or Research Centers. Dr. Hwang has performed consulting work with IBM, MIT Lincoln Lab, Chinese Academy of Sciences, and INRIA in France. He can be reached via his Email at USC: kaihwang@usc.edu.
Host: Shri Narayanan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Cathy Huang
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 Emerging Trends Seminar Series
Wed, Apr 26, 2017 @ 10:00 AM - 11:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Kai Hwang, Professor, Ming Hsieh Department of Electrical Engineering
Talk Title: Big-Data Analytics for Cloud Computing in Cognitive Applications
Series: Emerging Trends
Abstract: In this talk, Dr. Hwang will address the effective use of big-data analytics on smart clouds, social networks, intelligent robots, and IoT platforms. He will assess machine/deep learning models and available software tools to advance the cognitive service industry represented by Google, Microsoft, Apple, Facebook, Baidu, IBM, Huawei, etc. The ultimate goal is to achieve enhanced agility, mobility, security, and scalability of public clouds, IoT platforms, and social-media networks.
His talk will assess current AI programs and brain projects pursued by high-tech companies, including Google X-Lab, TensorFlow, DeepMind AlphaGo, Nvidia Digits 5 for using GPU in deep learning, IBM neuromorphic computer, and CAS/ICT Camericon project, etc. Some hidden R/D opportunities are revealed for building smart machines, delivery drones, self-driving cars, blockchains, AR/VR gears, etc. Extended cognitive applications will be discussed for 5G health-care, disease detection, emotion control, and social media community services.
Biography: Kai Hwang is a Professor of EE/CS at the Univ. of Southern California. He received his Ph.D. from UC Berkeley. He has published extensively in computer architecture, parallel processing, cloud computing, and network security. His latest two books are entitled: Cloud Computing for Machine Learning and Cognitive Applications (The MIT Press, April 2017) and Big Data Analytics for Cloud/IoT and Cognitive Computing (Wiley, U.K, May 2017).
An IEEE Life Fellow, he received the very first CFC Outstanding Achievement Award in 2004 and the Lifetime Achievement Award from IEEE Cloud2012 for his pioneering work in parallel computing and distributed systems. Four of his graduated Ph.D. students were elected as IEEE Fellows and one an IBM Fellow. He has delivered dozens of keynote or distinguished lectures in international Conferences or Research Centers. Dr. Hwang has performed consulting work with IBM, MIT Lincoln Lab, the Chinese Academy of Sciences, and INRIA in France. He can be reached via his Email at USC: kaihwang@usc.edu
Host: Shri Narayanan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Cathy Huang
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 CommNetS seminar
Wed, Apr 26, 2017 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Adam Wierman, Caltech
Talk Title: Platforms & Networked Markets: Transparency & Market Power
Series: CommNetS
Abstract: Platforms have emerged as a powerful economic force, driving both traditional markets, like the electricity market, and emerging markets, like the sharing economy. The power of platforms comes from their ability to tame the complexities of networked marketplaces -- marketplaces where there is not a single centralized market, but instead a network of interconnected markets loosely defined by a graph of feasible exchanges. Despite the power and prominence of platforms, the workings of platforms are often guarded secrets, e.g., we know little about how amazon matches buyers and seller and how uber matches drivers and riders. Further, many competing platforms make very different design choices, but little is understood about the impact of these differing choices. In this talk, I will overview recent work that focuses on reverse engineering the design of platforms and understanding the consequences of design choices underlying modern platforms. I will use electricity markets and ridesharing services as motivating examples throughout the talk.
Biography: Adam Wierman is a Professor in the Department of Computing and Mathematical Sciences at the California Institute of Technology, where he currently serves as Executive Officer. He is also the director of the Information Science and Technology (IST) initiative at Caltech. He is the founding director of the Rigorous Systems Research Group (RSRG) and co-Director of the Social and Information Sciences Laboratory (SISL). His research interests center around resource allocation and scheduling decisions in computer systems and services. He received the 2011 ACM SIGMETRICS Rising Star award, the 2014 IEEE Communications Society William R. Bennett Prize, and has been coauthor on papers that received of best paper awards at ACM SIGMETRICS, IEEE INFOCOM, IFIP Performance (twice), IEEE Green Computing Conference, IEEE Power & Energy Society General Meeting, and ACM GREENMETRICS. Additionally, he maintains a popular blog called Rigor + Relevance.
Host: Prof. Insoon Yang
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. -
Measurement and Analysis of Mobile and Social Networks
Thu, Apr 27, 2017 @ 11:00 AM - 12:15 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Athina Markopoulou, Professor/UC Irvine
Talk Title: Measurement and Analysis of Mobile and Social Networks
Abstract: The majority of Internet traffic today is through mobile devices and social media. Large-scale measurement and analysis of these systems is necessary in order to understand underlying patterns and enable engineering optimizations and new applications. In this talk, I will present highlights of our research in this area.
First, I will discuss online social networks. I will present our "2K+" framework for generating synthetic graphs that resemble online social networks, in terms of joint degree distribution and additional characteristics, such as clustering and node attributes [INFOCOM'13, INFOCOM'15]. This problem was motivated by our prior work on graph sampling [JSAC'11, SIGMETRICS'11, INFOCOM'10] and by popular demand to make the Facebook datasets we collected publicly available.
Second, I will discuss cellular networks. I will present our work on analyzing Call Detail Records (CDRs) in order to characterize human activity in urban environments, with applications to urban ecology [MOBIHOC'15] and ride-sharing [UBICOMP'14, SIGSPATIAL'15-16].
Third, I will present our ongoing work on AntMonitor - a system for monitoring network traffic on mobile devices [SIGCOMM C2BID'15], with applications to privacy leaks detection [MOBICOM Demo'15], crowdsourcing of network performance measurements, and improved wireless access.
Biography: Athina Markopoulou is an Associate Professor in EECS at the University of California, Irvine. She received the Diploma degree in Electrical and Computer Engineering from the National Technical University of Athens, Greece, in 1996, and the Master's and Ph.D. degrees in Electrical Engineering from Stanford University, in 1998 and 2003, respectively. She has held short-term/visiting appointments at SprintLabs (2003), Arista Networks (2005), IT University of Copenhagen (2012-2013), and she co-founded Shoelace Wireless (2012). She has received the NSF CAREER Award (2008), the Henry Samueli School of Engineering Faculty Midcareer Award for Research (2014), and the OCEC Educator Award (2017). She has been an Associate Editor for IEEE/ACM Transactions on Networking (2013-2015), an Associate Editor for ACM CCR (2016), the General Co-Chair for ACM CoNEXT 2016, and the Director of the Networked Systems program at UCI. Her research interests are in the area of networking including mobile systems and mobile data analytics, network measurement, online social networks, network security and privacy, network coding, and multimedia traffic.
Host: Professor Konstantinos Psounis, kpsounis@usc.edu
More Information: Seminar Announcement - Markopoulou 042717.pdf
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. -
PhD Defense
Thu, Apr 27, 2017 @ 01:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Akshay Gadde, University of Southern California
Talk Title: Sampling and Filtering of Signals on Graphs with Applications to Active Learning and Image Processing
Abstract: Processing of signals defined over the nodes of a graph has generated a lot of interest recently. This is due to the emergence of modern application domains such as social networks, web information analysis, sensor networks and machine learning, in which graphs provide a natural representation for the data. Traditional data such as images and videos can also be represented as signals on graphs. A frequency domain representation for graph signals can be obtained using the eigenvectors and eigenvalues of operators which measure the variation in signals taking into account the underlying connectivity in the graph. Spectral filtering can then be defined in this frequency domain. Based on this, we develop a sampling theory for graph signals by answering the following questions: 1. When can we uniquely and stably reconstruct a bandlimited graph signal from its samples on a subset of the nodes? 2. What is the best subset of nodes for sampling a signal so that the resulting bandlimited reconstruction is most stable? 3. How to compute a bandlimited reconstruction efficiently from a subset of samples? The algorithms developed for sampling set selection and reconstruction do not require explicit eigenvalue decomposition of the variation operator and admit efficient, localized implementation. Using graph sampling theory, we propose effective graph based active semi-supervised learning techniques. We also give a probabilistic interpretation for the proposed techniques. Based on this interpretation, we generalize the framework of active learning on graphs using Bayesian methods to give an adaptive sampling method. Additionally, we study the application graph spectral filtering in image processing by representing the image as a graph, where the nodes correspond to the pixels and edge weights capture the similarity between them given by the coefficients of the bilateral filter. We show that the bilateral filter is a low pass graph spectral filter with linearly decaying spectral response. We then generalize the bilateral filter by defining filters on the above graph with different spectral responses depending on the application. We also consider the problem of constructing a sparse graph from the given data efficiently, which can be used in graph based learning and fast image adaptive filtering.
Biography: Akshay Gadde received his Bachelor of Technology degree in Electrical Engineering from Indian Institute of Technology (IIT), Kharagpur, India in 2011. He has been working towards a Ph.D. in Electrical Engineering at the University of Southern California (USC), Los Angeles since 2011. His work (with Prof. Antonio Ortega and Aamir Anis) won the Best Student Paper Award at ICASSP 2014. His research interests include graph signal processing and machine learning with applications to multimedia data processing and compression.
Host: Dr. Antonio Ortega
More Information: Gadde Seminar Announcement.png
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Gloria Halfacre
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. -
Computer Architectures for Deep Learning Applications
Thu, Apr 27, 2017 @ 03:30 PM - 05:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: David Brooks, Harvard University
Talk Title: Computer Architectures for Deep Learning Applications
Abstract: Deep learning has been popularized by its recent successes on challenging artificial intelligence problems. One of the reasons for its dominance is also an ongoing challenge: the need for immense amounts of computational power. Hardware architects have responded by proposing a wide array of promising ideas, but to date, the majority of the work has focused on specific algorithms in somewhat narrow application domains. While their specificity does not diminish these approaches, there is a clear need for more flexible solutions. We believe the first step is to examine the characteristics of cutting edge models from across the deep learning community. Consequently, we have assembled Fathom: a collection of eight archetypal deep learning workloads for study. Each of these models comes from a seminal work in the deep learning community, ranging from the familiar deep convolutional neural network of Krizhevsky et al., to the more exotic memory networks from Facebook's AI research group. Fathom has been released online, and this talk describes the fundamental performance characteristics of each model. We use a set of application-level modeling tools built around the TensorFlow deep learning framework in order to analyze the behavior of the Fathom workloads. We present a breakdown of where time is spent, the similarities between the performance profiles of our models, an analysis of behavior in inference and training, and the effects of parallelism on scaling. The talk will then consider novel computer architectures that can improve the performance and efficiency of deep learning workloads.
Biography: David Brooks is the Haley Family Professor of Computer Science in the School of Engineering and Applied Sciences at Harvard University. Prior to joining Harvard, he was a research staff member at IBM T.J. Watson Research Center. Prof. Brooks received his BS in Electrical Engineering at the University of Southern California and MA and PhD degrees in Electrical Engineering at Princeton University. His research interests include resilient and power-efficient computer hardware and software design for high-performance and embedded systems. Prof. Brooks is a Fellow of the IEEE and has received several honors and awards including the ACM Maurice Wilkes Award, ISCA Influential Paper Award, NSF CAREER award, IBM Faculty Partnership Award, and DARPA Young Faculty Award.
Host: Xuehai Qian, x04459, xuehai.qian@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.
