SUNMONTUEWEDTHUFRISAT
Events for November
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Center for Cyber-Physical Systems and Internet of Things and Ming Hsieh Institute Distinguished Seminar
Mon, Nov 04, 2019 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Professor Stephen Boyd, Electrical Engineering, Stanford University
Talk Title: Convex Optimization
Series: Cyber-Physical Systems Joint Seminar Series
Abstract: Convex optimization has emerged as useful tool for applications that includedata analysis and model fitting, resource allocation, engineering design, network design and optimization, finance, and control and signal processing. After an overview of the mathematics, algorithms, and software frameworks for convex optimization, we turn to common theme that arise across applications, such as sparsity and relaxation. We describe recent work on real-time embedded convex optimization, in which small problems are solved repeatedly in millisecond or microsecond time frames, and large-scale distributed convex optimization, in which many solvers are coordinated to solve enormous problems.
Biography: Stephen P. Boyd is the Samsung Professor of Engineering, Professor of Electrical Engineering in the Information Systems Laboratory, and chair of the Electrical Engineering Department at Stanford University. He has courtesy appointments in the Department of Management Science and Engineering and the Department of Computer Science, and is a member of the Institute for Computational and Mathematical Engineering. His current research focus is on convex optimization applications in control, signal processing, machine learning, and finance.
Professor Boyd received an AB degree in Mathematics, summa cum laude, from Harvard University in 1980, and a PhD in EECS from U. C. Berkeley in 1985. In 1985 he joined the faculty of Stanford's Electrical Engineering Department. He has held visiting Professor positions at Katholieke University (Leuven), McGill University (Montreal), Ecole Polytechnique Federale (Lausanne), Tsinghua University (Beijing), Universite Paul Sabatier (Toulouse), Royal Institute of Technology (Stockholm), Kyoto University, Harbin Institute of Technology, NYU, MIT, UC Berkeley, CUHK-Shenzhen, City University of Hong Kong, and IMT Lucca. He holds honorary doctorates from Royal Institute of Technology (KTH), Stockholm, and Catholic University of Louvain (UCL).
Professor Boyd has received many awards and honors for his research in control systems engineering and optimization, including an ONR Young Investigator Award, a Presidential Young Investigator Award, and the AACC Donald P. Eckman Award. In 2013, he received the IEEE Control Systems Award, given for outstanding contributions to control systems engineering, science, or technology. In 2012, Michael Grant and he were given the Mathematical Optimization Society's Beale-Orchard-Hays Award, given every three years for excellence in computational mathematical programming. He is a Fellow of the IEEE, SIAM, and INFORMS, a Distinguished Lecturer of the IEEE Control Systems Society, a member of the US National Academy of Engineering, and a foreign member of the Chinese Academy of Engineering. He has been invited to deliver more than 90 plenary and keynote lectures at major conferences in control, optimization, signal processing, and machine learning.
At Stanford, he has served as director of the Information Systems Laboratory, chair of the (university wide) Library Committee, chair of the David Packard EE Building Planning & Design Committee, and as a member of the (university wide) Advisory Board.
Host: Paul Bogdan, pbogdan@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Talyia White
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Center for Cyber-Physical Systems and Internet of Things and Ming Hsieh Institute Seminar
Wed, Nov 06, 2019 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Prabal Dutta, University of California, Berkeley
Talk Title: Enabling the SmartGrid with IoT Sensors and Edge-Cloud Analytics
Series: Center for Cyber-Physical Systems and Internet of Things
Abstract: Wireless sensors and edge-cloud analytics have the potential to gather and process vast amounts of data about the physical world, offering radical new insights about everything from critical infrastructure to interpersonal interactions. But designing, deploying, and operating geographically-distributed systems consisting a hierarchy of sensing, storage, compute, and communication elements raises interesting new challenges across the system stack. In this talk, we will discuss our experiences designing new IoT systems to address several power and power grid monitoring problems. In particular, this talk will focus on three systems-”PowerBlade, Triumvi, and GridWatch-”and their motivation, design, and deployment. PowerBlade explores how to cost-effectively characterize, capture, and classify widespread plug-load energy usage-”representing the fastest growing and least understood segment of end-use energy consumption-”across hundreds of homes and offices representing tens of thousands of sensors. Triumvi explores how to make circuit level energy metering, useful for a variety of facilities trending, energy savings, and fault detection & diagnostics applications, more efficient and scalable. Finally, GridWatch explores how to scalably and cost-effectively detect and respond to the power outages that stymie residential and business activity in under-developed power grids using mobile and fixed sensors, data analytics, and reporting systems in Sub-Saharan Africa, finding that conventional approaches to outage detection systems vastly underreport customer experiences. These systems all share a similar architecture, require new sensor devices and edge-cloud data processing, and wrestle with power management and networking. But they ultimately demonstrate both the tremendous potential and the significant challenges of this nascent computing class.
Biography: Prabal Dutta is an Associate Professor of Electrical Engineering and Computer Sciences at the University of Calfornia at Berkeley, where he co-directors the CONIX Research Center. Previously, he was a Morris Wellman Faculty Development Associate Professor of Electrical Engineering and Computer Science at the University of Michigan. His interests span circuits, systems, and software, with a focus on mobile, wireless, embedded, networked, and sensing systems with applications to health, energy, and the environment. His work has yielded dozens of hardware and software systems, has won five Top Pick/Best Paper Awards, two Best Paper Nominations, and a Potential Test of Time 2025 Award, as well as several demo, design, and industry competitions. His work has been directly commercialized by a dozen companies and indirectly by many dozens more, has been utilized by thousands of researchers and practitioners worldwide, and is on display at Silicon Valley's Computer History Museum.
His research has been recognized with an Alfred P. Sloan Research Fellowship, an NSF CAREER Award, a Popular Science Brilliant Ten Award, an Intel Early Career Faculty Fellowship, and as a Microsoft Research Faculty Fellowship Finalist. He has served as chair or co-chair of MobiSys '18, BuildSys '17, IPSN '17, ESWEEK '17 IoT Day, HotMobile '16, SenSys '14, and HotPower '11, and on the DARPA ISAT Study Group from 2012-2016, where he co-chaired numerous studies. He holds a Ph.D. in Computer Science from UC Berkeley (2009), where NSF and Microsoft Research Graduate Fellowships supported his research. He received an M.S. in Electrical Engineering (2004) and a B.S. Electrical and Computer Engineering (1997), both from The Ohio State University. Website: http://www.eecs.berkeley.edu/~prabal
Host: Paul Bogdan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Talyia White
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Medical Imaging Seminar
Thu, Nov 07, 2019 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Xucheng Zhu, University of California, Berkeley
Talk Title: 3D Free Breathing Pediatric Pulmonary MRI
Series: Medical Imaging Seminar Series
Abstract: In contrast to PET and CT, MRI delivers no ionizing radiation and within a single imaging session provides a wide range of soft tissue characterization and function. Unfortunately, the innumerable air-tissue interfaces in the lung disrupt the MRI signal, rendering lung tissue invisible on conventional MRI. Furthermore, scans are highly susceptible to respiratory and bulk motion that is widely prevalent in pediatric patient populations. For these reasons, MRI is currently insufficient to provide the prognostic and diagnostic information required of imaging studies. We proposed a novel motion corrected imaging framework, combining with a ultra-short echo time(UTE) acquisition to overcome the existing challenges in pediatric lung MRI.
Biography: Xucheng Zhu is a 5th year PhD student in the joint UC Berkeley and UCSF Bioengineering program, mentored by Dr. Peder Larson. My PhD thesis focuses on 3D high resolution free breathing lung MRI. I also have experience in PET/MR reconstruction and motion correction, dynamic hyperpolarized 13C MRI, and deep learning based medical image enhancement.
Host: Professor Krishna Nayak, knayak@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Talyia White
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*CANCELLED* Fall 2019 Joint CSC@USC/CommNetS-MHI Seminar Series
Mon, Nov 11, 2019 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Andrea Serrani, Ohio State University
Talk Title: *THIS TALK IS CANCELLED* -- A Geometric Viewpoint on Dynamic Control Allocation
Abstract: Input redundancy in a control system is typically resolved by means of (static) control allocation strategies, where the standing assumptions prescribe that one can define a virtual control input that has the same dimensionality of the regulated output. A control strategy designed on the basis of this virtual input is then distributed across the redundant set of actuators via on-line optimization. Essentially, this scenario confines redundancy to the null-space of the input operator, which can be factored out by projection. On the other hand, for the case of input redundancy with full-rank input operators, multiple independently controllable state-trajectories exist that are compatible with a given reference output. In this talk, a comprehensive geometric characterization of input redundant linear systems is offered. It is shown that intrinsic input redundancy can be exploited in the system inverse rather than in the plant model itself, leading to the definition of novel dynamic control allocation strategies. In the proposed scheme, the steady-state behavior of the system is shaped through dynamic optimization of selected performance criteria penalizing both the control input and the state trajectory, while maintaining invariance of the error-zeroing subspace. Illustrative examples are presented to elucidate the applicability and the significance of the method.
Biography: Andrea Serrani received the Ph.D. degree in Artificial Intelligence Systems from the University of Ancona, Italy, in 1997 and the D.Sc. degree in Systems Science and Mathematics from Washington University in Saint Louis in 2000. Since 2002, he has been with the Department of Electrical and Computer Engineering at The Ohio State University, Columbus, Ohio, where he is currently a Professor and Associate Chair. His research activity spans the fields of control and systems theory, with emphasis on nonlinear and adaptive control, tracking and regulation, and application to aerospace and automotive systems. His latest interests include modeling and control of flapping-wing micro-air vehicles, control of multi-actuated powertrain systems, and guidance and control of hypersonic vehicles. He is the author of more than 150 journal and conference publications, and the co-author (with A. Isidori and L. Marconi) of the book Robust Autonomous Guidance - An Internal Model Approach, published by Springer Verlag. Prof. Serrani serves as the Editor-in-Chief of the IEEE Transactions on Control Systems Technology, and as an Associate Editor the IEEE CSS and IFAC Conference Editorial Boards. He is a past Associate Editor for Automatica and the International Journal of Robust and Nonlinear Control. He was the Program Chair of the 2019 American Control Conference and the General Co-Chair for the 2022 IEEE Conference on Decision and Control.
Host: Mihailo Jovanovic, mihailo@usc.edu
More Info: http://csc.usc.edu/seminars/2019Fall/serrani.html
More Information: 191111_Andrea Serrani_CSC.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Brienne Moore
Event Link: http://csc.usc.edu/seminars/2019Fall/serrani.html
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Center for Cyber-Physical Systems and Internet of Things and Ming Hsieh Institute Seminar
Wed, Nov 13, 2019 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Nikil Dutt, Distinguished Professor, University of California, Irvine
Talk Title: Computational Self-awareness and Self-organization: A Paradigm for Building Adaptive, Resilient Computing Platforms
Series: Center for Cyber-Physical Systems and Internet of Things
Abstract: Self-awareness and self-organization have a long history in biology, psychology, medicine, engineering and (more recently) computing. In the past decade this has inspired new self-aware/self-organizing strategies for building resilient computing platforms that can adapt to the (often conflicting) challenges of resiliency, energy, heat, cost, performance, security, etc. in the face of highly dynamic operational behaviors and environmental conditions. I will begin by outlining a computational self-awareness paradigm that enables adaptivity and which supports system resilience. I will show how computational self-awareness can be deployed to achieve cross-layer resilience on the exemplar CyberPhysical-Systems-on-Chip (CPSoC) platform. CPSoC is a new class of sensor-actuator rich many-core computing platform that intrinsically couples on-chip and cross-layer sensing and actuation to support computational self-awareness. Computational self-awareness is achieved through introspection (i.e., modeling and observing its own internal and external behaviors) combined with both reflexive and reflective adaptations via cross-layer physical and virtual sensing and actuations applied across multiple layers of the hardware/software system stack. Next I will outline strategies for combining computational self-awareness with self-organization for life-cycle management of dependable distributed computing platforms. Our ongoing NSF/DFG Information Processing Factory (IPF) project applies principles inspired by factory management that combine self-awareness and self-organization for continuous operation and optimization of highly-integrated-but-distributed embedded computing platforms. While each IPF computational component exhibits autonomy through self-awareness, collections of IPF entities can self-organize; the resulting emergent behavior must be controlled in order to ensure guaranteed service even under strict safety and availability requirements. I will outline strategies such as proactive reconfiguration to mitigate the risk of failures, self-optimization, self-identification using learning classifiers, and chip-level operation with flexible boundaries between critical and best effort regions, all guided by a self-aware planning component. The talk will conclude with the opportunities and challenges arising from adopting computational self-awareness and self-organization for making complex computational systems more resilient and self-adaptive.
Biography: Nikil Dutt is a Distinguished Professor of CS, Cognitive Sciences, and EECS at the University of California, Irvine, and also a Distinguished Visiting Professor of CSE at IIT Bombay, India. He received a PhD from the University of Illinois at Urbana-Champaign (1989). His research interests are in embedded systems, EDA, computer architecture and compilers, distributed systems, healthcare IoT, and brain-inspired architectures and computing. He has received numerous best paper awards and is coauthor of 7 books. Professor Dutt has served as EiC of ACM TODAES and AE for ACM TECS and IEEE TVLSI. He is on the steering, organizing, and program committees of several premier EDA and Embedded System Design conferences and workshops, and has also been on the advisory boards of ACM SIGBED, ACM SIGDA, ACM TECS and IEEE ESL. He is an ACM Fellow, IEEE Fellow, and recipient of the IFIP Silver Core Award.
Host: Jyotirmoy Deshmukh
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Talyia White
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Processing in Memory (PIM) – Power and Thermal Challenges and Opportunities
Fri, Nov 15, 2019 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Mircea Stan, University of Virginia
Talk Title: Processing in Memory (PIM) -“ Power and Thermal Challenges and Opportunities
Abstract: Memory technology is a defining component of modern computing and has a strong impact on performance, power and cost of computing systems. However, the advances in memory performance have not been able to keep up with the performance advances for CPUs, thus leading to what is known as the memory wall. Depending on the application, the memory wall manifests itself both in terms of memory latency, as well as memory bandwidth. An interesting solution to the memory wall problem is to bring memory closer to the processor, or vice-versa, to move some processing capability in the memory itself -“ this leads to variations of what is known as Near-Memory Processing, Processing in Memory (PiM), etc. This seminar will first introduce a PIM taxonomy along several dimensions of the PiM design space; it will then follow with a history of PIM, then go over several recent PIM examples. The seminar will then go in-depth into the Thermal/Power delivery challenges for PIM that are a result of the increased switching activities inherent to the moving of processing into the memory fabric, and exacerbated by the evolution towards 3D integration due to the slow-down of traditional Moore law methods. The seminar will conclude with some novel solutions that alleviate the Thermal/Power challenges for PiM.
Biography: Mircea R. Stan received the Ph.D. (1996) and the M.S. (1994) degrees from UMass Amherst and the Diploma (1984) from the Polytechnic Institute in Bucharest, Romania. Since 1996 he has been with the ECE Department at UVa, where he is now the Virginia Microelectronics Consortium (VMEC) Professor. Prof. Stan is teaching and doing research in the areas of high-performance low-power VLSI, temperature-aware circuits and architecture, embedded systems, spintronics, and nanoelectronics. He leads the High-Performance Low-Power (HPLP) lab, is an associate director of the Center for Automata Processing (CAP) and an assistant director of the Center for Research in Intelligent Storage and Processing-in-Memory (CRISP). He was a visiting faculty at UC Berkeley in 2004-2005, at IBM in 2000, and at Intel in 2002 and 1999. He received the 2018 Influential ISCA Paper Award (For 2003 paper Temperature-aware microarchitecture), the NSF CAREER award in 1997 and was a co-author on best paper awards at LASCAS19, SELSE17, ISQED08, GLSVLSI06, ISCA03 and SHAMAN02 and IEEE Micro Top Picks in 2008 and 2003. He gave keynotes at DCAS18, SOCC16, CogArch16, WoNDP15, iNIS15 and CNNA14. He was the chair of the VSA-TC of IEEE CAS in 2005-2007, general chair for ISLPED06 and GLSVLSI04, TPC chair for SOCC18, ISVLSI17, NanoNets07 and ISLPED05, and on technical committees for numerous conferences. He is Associate Editor-in-Chief for the IEEE TVLSI, Senior Editor for the IEEE TNano, AE for IEEE Design & Test, and was an AE for the IEEE TNano in 2012-2014, IEEE TCAS I in 2004-2008 and for the IEEE TVLSI in 2001-2003. Prof. Stan is a fellow of the IEEE, a member of ACM, and of Eta Kappa Nu, Phi Kappa Phi and Sigma Xi.
Host: Xuehai Qian, xuehai.qian@usc.edu
More Information: 191115_Mircea Stan_CENG.pdf
Location: Ronald Tutor Hall of Engineering (RTH) - 211
Audiences: Everyone Is Invited
Contact: Brienne Moore
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Fall 2019 Joint CSC@USC/CommNetS-MHI Seminar Series
Mon, Nov 18, 2019 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Steven Brunton, University of Washington
Talk Title: Machine Learning and Sparse Optimization for Modeling, Sensing, and Controlling Fluid Dynamics
Abstract: Many tasks in fluid mechanics, such as design optimization, sensor selection, modeling, and control, are challenging because fluids are nonlinear and exhibit a large range of scales in both space and time. This range of scales necessitates exceedingly high-dimensional measurements and computational discretization to resolve all relevant features, resulting in vast data sets and time-intensive computations. Indeed, fluid dynamics is one of the original big data fields, and many high-performance computing architectures, experimental measurement techniques, and advanced data processing and visualization algorithms were driven by decades of research in fluid mechanics. Despite the increasing volumes of fluid data, low-dimensional patterns often exist, and there are considerable efforts to model the evolution of these dominant coherent structures that are important for engineering objectives. In this talk, I will explore a number of emerging techniques in machine learning and sparse optimization that complement existing numerical and experimental efforts in fluid mechanics. Machine learning comprises a powerful set of techniques to uncover these low-dimensional flow patterns, which in turn enables sparse optimization for efficient sampling and computations. The resulting models are parsimonious, balancing model complexity with descriptive ability while avoiding overfitting. Because fluid dynamics is central to transportation, health, energy, and defense systems, I will emphasize the importance of machine learning solutions that are interpretable, generalizable, and that respect known physics.
Biography: Steven L. Brunton is the James B. Morrison Associate Professor of Mechanical Engineering at the University of Washington. He is also Adjunct Associate Professor of Applied Mathematics and a Data Science Fellow at the eScience Institute. Steve received the B.S. in mathematics from Caltech in 2006 and the Ph.D. in mechanical and aerospace engineering from Princeton in 2012. His research combines machine learning with dynamical systems to model and control systems in fluid dynamics, biolocomotion, optics, energy systems, and manufacturing. He is a co-author of three textbooks, received the Army and Air Force Young Investigator Program (YIP) awards, and the Presidential Early Career Award for Scientists and Engineers (PECASE).
Host: Prof. Si-Zhao Qin, sqin@usc.edu
More Info: http://csc.usc.edu/seminars/2019Fall/brunton.html
More Information: 191118_Steven Brunton_CSC.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Brienne Moore
Event Link: http://csc.usc.edu/seminars/2019Fall/brunton.html
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CILQ Faculty Seminar
Mon, Nov 18, 2019 @ 04:00 PM - 05:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Alan Willner, Professor/USC
Talk Title: High-Capacity Free-Space Communication Links Using Mode-Division Multiplexing
Abstract: Multiple orthogonal beams, each located on a different spatial mode and carrying independent data, can be simultaneously transmitted between two apertures. This form of spatial multiplexing, known as mode multiplexing, has the potential to significantly increase communication system capacity and spectral efficiency. Of particular note is the multiplexing of orbital-angular-momentum modes for high-capacity free-space optical and millimeter-wave links. We will discuss transmission results, design guidelines, mitigation of turbulence and crosstalk, and classical and quantum channels.
Host: CSI
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Corine Wong
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Ming Hsieh Institute Seminar Series on Integrated Systems
Fri, Nov 22, 2019 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Firooz Aflatouni, Skirkanich Assistant Professor, University of Pennsylvania
Talk Title: Electronic-photonic Co-design; from Imaging to Optical Phase Control
Host: Profs. Hossein Hashemi, Mike Chen, Dina El-Damak, Manuel Monge, Constantine Sideris, and Mahta Moghaddam
More Information: MHI Seminar Series IS - Firooz Aflatouni.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Jenny Lin
