Events for the 2nd week of April
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EE-EP Faculty Candidate, Negar Reiskarimian - Monday, April 9th at 12pm in EEB 132
Mon, Apr 09, 2018 @ 12:00 PM - 01:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Negar Reiskarimian, Columbia University
Talk Title: Breaking Lorentz Reciprocity: From New Physical Concepts to Applications
Abstract: Lorentz reciprocity is a fundamental characteristic of the vast majority of electronic and photonic structures. However, breaking reciprocity enables the realization of non-reciprocal components, such as isolators and circulators, which are critical to electronic and optical communication systems, as well as new components and functionalities based on novel wave propagation modes. In this talk, I will present a novel approach to break Lorentz reciprocity based on linear periodically-time-varying (LPTV) circuits. We have demonstrated the world's first CMOS passive magnetic-free non-reciprocal circulator through spatio-temporal conductivity modulation. Since conductivity in semiconductors can be modulated over a much wider range than the more traditionally exploited permittivity, our structure is able to break reciprocity within a compact form factor with very low loss and high linearity. I will discuss fundamental limits of space-time modulated nonreciprocal structures, as well as new directions to build non-reciprocal components which can ideally be infinitesimal in size. Furthermore, I cover some of the applications of nonreciprocal components in wireless communication systems.
Looking to the future, I am broadly interested in exploring novel fundamental physical concepts that have strong engineering applications. I wish to work in an interdisciplinary area between integrated circuit design and closely related fields such as applied physics, applied electromagnetics and nanophotonics, and to identify and investigate ideas and concepts that can best be implemented using the semiconductor platform. Finally, I will share with you some examples of the exciting research directions I would like to pursue with the aim of participating in building the next generation of technologies that augment human lives.
Biography: Negar Reiskarimian received the Bachelor's and Master's degrees in electrical engineering from Sharif University of Technology in Iran, and is currently a PhD candidate in Electrical Engineering at Columbia University. She has published in top-tier IEEE IC-related journals and conferences, as well as broader-interest high-impact journals in the Nature family. Her research has been widely covered in the press, and featured in IEEE Spectrum, Gizmodo and EE Times among others. She is the recipient of numerous awards and fellowships, including Forbes 30 under 30, Paul Baran Young Scholar, Qualcomm Innovation Fellowship and multiple IEEE societies awards and fellowships.
Host: EE-Electrophysics
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
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Center for Systems and Control (CSC@USC) and Ming Hsieh Institute for Electrical Engineering
Mon, Apr 09, 2018 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Anders Rantzer, Lund University
Talk Title: Towards a Scalable Theory of Control
Series: Joint CSC@USC/CommNetS-MHI Seminar Series
Abstract: Classical control theory does not scale well for large systems like traffic networks, power networks and chemical reaction networks. To change this situation, new approaches need to be developed, not only for analysis and synthesis of controllers, but also for modelling and verification. In this lecture we will present a class of networked control problems for which scalable distributed controllers can be proved to achieve the same performance as the best centralized ones. The control objective is stated in terms of frequency weighted H-infinity norms, which makes it possible to combine disturbance rejection at low frequencies with robustness to high frequency measurement noise and model errors. An optimal controller is given in the form of a multi-variable PI controller, which is distributed in the sense that control action along a given network edge is entirely determined by states at nodes connected by that edge. We will discuss some application examples, as well as connections to other aspects of scalability.
Biography: Anders Rantzer received a PhD in 1991 from KTH, Stockholm, Sweden. After postdoctoral positions at KTH and at IMA, University of Minnesota, he joined Lund University in 1993 and was appointed professor of Automatic Control in 1999. During the academic year of 2004-2005 he was visiting associate faculty member at Caltech and 2015-2016 he was Taylor Family Distinguished Visiting Professor at the University of Minnesota. Since 2008 he coordinates the Linnaeus center LCCC at Lund University.
Professor Rantzer is an editorial board member of Proceedings of the IEEE and several other publications. He is a winner of the SIAM Student Paper Competition, the IFAC Congress Young Author Price, and the award for best article in IEE Proceedings - Control Theory and Applications. He is a Fellow of IEEE, a member of the Royal Swedish Academy of Engineering Sciences, and former chairman of the Swedish Scientific Council for Natural and Engineering Sciences.
His research interests are in modeling, analysis and synthesis of control systems, with particular attention to uncertainty, optimization, scalability and adaptation.
Host: Mihailo Jovanovic, mihailo@usc.edu
More Information: rantzer.jpg (JPEG Image, 300 × 400 pixels).pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Gerrielyn Ramos
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EE Seminar: Analysis, Design, and Operation of Secure Cyber-Physical Systems
Tue, Apr 10, 2018 @ 03:00 PM - 04:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Fabio Pasqualetti, Assistant Professor, University of California, Riverside
Talk Title: Analysis, Design, and Operation of Secure Cyber-Physical Systems
Abstract: Today's cyber-physical systems are the building blocks of smart and citizen-centric applications that will revolutionize the way people interact with the urban environment. Smart systems, cities, and communities will emerge, in which advanced levels of autonomy hold the promise of greater efficiency, reliability and sustainability in areas of national interest and social need, such as health, energy, and transportation. In this new realm of applications, however, enhanced connectivity and advanced autonomy will also pose novel and significant risks to people and the infrastructure, including safety, security, and privacy.
In this talk, I present a unified framework for the analysis of fundamental vulnerabilities affecting cyber-physical systems, the design of targeted detection and protection schemes, and the construction of systems that are provably resilient to accidental malfunctions and malicious attacks. I show how cyber-physical security differs from well-established disciplines, including cyber security and fault tolerance, and how our control- and graph-theoretic methods complement existing security practices to fully protect cyber-physical systems. Further, I reveal a novel class of integrity attacks against smart power grids, and show how these attacks lead to the formulation of novel sparse network control problems, which we also solve. Finally, I discuss directions of future research and open questions in cyber-physical security.
Biography: Fabio Pasqualetti is an Assistant Professor in the Department of Mechanical Engineering, University of California, Riverside. He completed a Doctor of Philosophy degree in Mechanical Engineering at the University of California, Santa Barbara, in 2012, a Laurea Magistrale degree (M.Sc. equivalent) in Automation Engineering at the University of Pisa, Italy, in 2007, and a Laurea degree (B.Sc. equivalent) in Computer Engineering at the University of Pisa, Italy, in 2004. He received a Young Investigator Program award from ARO in 2017, and the 2016 TCNS Outstanding Paper Award from IEEE CSS. His main research interest is in secure control systems, with application to multi-agent networks, distributed computing, and power networks. Other interests include computational neuroscience, vehicle routing, and combinatorial optimization.
Host: Mihailo Jovanovic, mihailo@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
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Research and Technology Seminar
Wed, Apr 11, 2018 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Sunil Bharitkar, Distinguished Member of Tech. Staff (HP Labs)
Talk Title: Advances in Joint Signal Processing, Perception, and Machine Learning at HP Labs
Abstract: In HP's Emerging Compute Lab, research is being conducted at the intersection of signal processing, auditory perception and machine learning to create fundamentally new experiences for differentiation in HP devices including VR HMD. In this talk we will present various techniques and algorithms, incorporating knowledge of binaural perception, machine learning, and signal processing, to enhance low-frequency perception, spatial rendering, and automated content classification. The research results have been validated through perceptual testing in large-scale studies giving statistically meaningful results. Ongoing research being conducted in the areas deep learning (stacked autoencoders and LSTM) for VR head-related transfer function synthesis, content classification, speech and multimodal biometrics, sensing towards emotion interpretation, and cancer cell data classification (jointly with Life Sciences Lab) will also be presented. The presentation will be accompanied with demonstrations.
Biography: Sunil Bharitkar received his Ph.D. in Electrical Engineering from the University of Southern California (USC) in 2004 and is involved in research in speech/audio analysis and processing including spatial audio for AR/VR, biometric & biomedical signal processing, multimodal signal processing, and machine learning. From 2011-2016 he was at Dolby leading/guiding research in audio, signal processing, haptics, machine learning, hearing augmentation, and standardization activities at ITU, SMPTE, AES. He co-founded the company Audyssey Laboratories in 2002 where he was VP of Research and responsible for inventing new technologies which were licensed to companies including IMAX, Denon, Audi, Sharp, etc. He also taught in the Department of Electrical Engineering at USC. Sunil has published over 50 technical papers and has over 20 patents in the area of signal processing applied to acoustics, neural networks and pattern recognition, and a textbook (Immersive Audio Signal Processing) from Springer-Verlag. He is a reviewer for papers at various conferences and journals. He has also been on the Organizing and Technical Program Committees of various conferences such as the 2008 and 2009 European Sig. Proc. Conference (EUSIPCO), the 57th AES Conference, SMPTE Conferences. He has also served as an invited tutorial speaker at the 2006 IEEE Conf. on Acoustics Speech and Signal Processing (ICASSP). He is a Senior Member of the IEEE, the Acoustical Soc. of America (ASA), European Association for Signal and Image Processing (EURASIP), and the Audio Eng. Soc. (AES). Sunil is a PADI diver and enjoys playing the Didgeridoo.
Host: Panos Georgiou and Shri Narayanan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Cathy Huang
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From Gaussian Multiterminal Source Coding to Distributed Karhunen Loève Transform
Wed, Apr 11, 2018 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Jun Chen, Department of Electrical and Computer Engineering, McMaster University
Talk Title: From Gaussian Multiterminal Source Coding to Distributed Karhunen Loève Transform
Series: Joint Seminar Series Seminar Series on Cyber-Physical Systems and CommNetS-MHI Seminar Series
Abstract: Characterizing the rate-distortion region of Gaussian multiterminal source coding is a longstanding open problem in network information theory. In this talk, I will show how to obtain new conclusive results for this problem using nonlinear analysis and convex relaxation techniques. A byproduct of this line of research is an efficient algorithm for determining the optimal distributed Karhunen-“Loève transform in the high-resolution regime, which partially settles a question posed by Gastpar, Dragotti, and Vetterli. I will also introduce a generalized version of the Gaussian multiterminal source coding problem where the source-encoder connections can be arbitrary. It will be demonstrated that probabilistic graphical models offer an ideal mathematical language for describing how the performance limit of a generalized Gaussian multiterminal source coding system depends on its topology, and more generally they can serve as the long-sought platform for systematically integrating the existing achievability schemes and converse arguments. The architectural implication of our work for low-latency lossy source coding will also be discussed. This talk is based on joint work with Jia Wang, Farrokh Etezadi, and Ashish Khisti.
Biography: Jun Chen received the B.E. degree with honors in communication engineering from Shanghai Jiao Tong University, Shanghai, China, in 2001 and the M.S. and Ph.D. degrees in electrical and computer engineering from Cornell University, Ithaca, NY, in 2004 and 2006, respectively. He was a Postdoctoral Research Associate in the Coordinated Science Laboratory at the University of Illinois at Urbana-Champaign, Urbana, IL, from September 2005 to July 2006, and a Postdoctoral Fellow at the IBM Thomas J. Watson Research Center, Yorktown Heights, NY, from July 2006 to August 2007. Since September 2007 he has been with the Department of Electrical and Computer Engineering at McMaster University, Hamilton, ON, Canada, where he is currently an Associate Professor and a Joseph Ip Distinguished Engineering Fellow. His research interests include information theory, machine learning, wireless communications, and signal processing. He received the Josef Raviv Memorial Postdoctoral Fellowship in 2006, the Early Researcher Award from the Province of Ontario in 2010, and the IBM Faculty Award in 2010. He served as an Associate Editor for the IEEE Transactions on Information Theory from 2014 to 2016.
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Talyia White
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EE Seminar: Towards Generalizable Imitation in Robotics
Thu, Apr 12, 2018 @ 01:30 PM - 02:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Animesh Garg, Postdoctoral Researcher, Stanford University AI lab
Talk Title: Towards Generalizable Imitation in Robotics
Abstract: Robotics and AI are experiencing radical growth, fueled by innovations in data-driven learning paradigms coupled with novel device design, in applications such as healthcare, manufacturing and service robotics. And in our quest for general purpose autonomy, we need abstractions and algorithms for efficient generalization.
Data-driven methods such as reinforcement learning circumvent hand-tuned feature engineering, albeit lack guarantees and often incur a massive computational expense: training these models frequently takes weeks in addition to months of task-specific data-collection on physical systems. Further such ab initio methods often do not scale to complex sequential tasks. In contrast, biological agents can often learn faster not only through self-supervision but also through imitation. My research aims to bridge this gap and enable generalizable imitation for robot autonomy. We need to build systems that can capture semantic task structures that promote sample efficiency and can generalize to new task instances across visual, dynamical or semantic variations. And this involves designing algorithms that unify in reinforcement learning, control theoretic planning, semantic scene & video understanding, and design.
In this talk, I will discuss two aspects of Generalizable Imitation: Task Imitation, and Generalization in both Visual and Kinematic spaces. First, I will describe how we can move away from hand-designed finite state machines by unsupervised structure learning for complex multi-step sequential tasks. Then I will discuss techniques for robust policy learning to handle generalization across unseen dynamics. I will revisit structure learning for task-level understanding for generalization to visual semantics.
And lastly, I will present a program synthesis based method for generalization across task semantics with a single example with unseen task structure, topology or length. The algorithms and techniques introduced are applicable across domains in robotics; in this talk, I will exemplify these ideas through my work on medical and personal robotics.
Biography: Animesh is a Postdoctoral Researcher at Stanford University AI lab. Animesh is interested in problems at the intersection of optimization, machine learning, and design. He studies the interaction of data-driven Learning for autonomy and Design for automation for human skill-augmentation and decision support. Animesh received his Ph.D. from the University of California, Berkeley where he was a part of the Berkeley AI Research center and the Automation Science Lab. His research has been recognized with Best Applications Paper Award at IEEE CASE, Best Video at Hamlyn Symposium on Surgical Robotics, and Best Paper Nomination at IEEE ICRA 2015. And his work has also featured in press outlets such as New York Times, UC Health, UC CITRIS News, and BBC Click.
Host: Pierluigi Nuzzo, nuzzo@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
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2018 Viterbi Keynote Lecture
Thu, Apr 12, 2018 @ 04:00 PM - 05:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: David Tse, Thomas Kailath and Guanghan Xu Professor, Stanford University
Talk Title: Maximum likelihood Genome Sequencing
Series: Viterbi Lecture
Abstract: Genome sequencing is one of the biggest breakthroughs in science in the past two decades. Modern sequencing methods use linking data at multiple scales to reconstruct pertinent information about the genome. Many such reconstruction problems can be formulated as maximum likelihood sequence decoding from noisy linking data. We discuss two in this talk: haplotype phasing, the problem of sequencing genomic variations on each of the maternal and paternal chromosomes, and genome scaffolding, the problem of finishing genome assembly using long-range 3D contact data. While maximum likelihood sequence decoding is NP-hard in both of these problems, spectral and linear programming relaxations yield efficient approximation algorithms that can provably achieve the information theoretic limits and perform well on real data. These results parallel the biggest success of information theory: efficiently achieving the fundamental limits of communication.
Biography: David Tse received the B.A.Sc. degree in systems design engineering from University of Waterloo in 1989, and the M.S. and Ph.D. degrees in electrical engineering from Massachusetts Institute of Technology in 1991 and 1994 respectively. From 1995 to 2014, he was on the faculty of the University of California at Berkeley. He received the Claude E. Shannon Award in 2017 and was elected member of the U.S. National Academy of Engineering in 2018. Previously, he received a NSF CAREER award in 1998, the Erlang Prize from the INFORMS Applied Probability Society in 2000 and the Frederick Emmons Terman Award from the American Society for Engineering Education in 2009. He received multiple best paper awards, and is the inventor of the proportional-fair scheduling algorithm used in all third and fourth-generation cellular systems.
Host: Sandeep Gupta, sandeep@usc.edu
More Info: https://minghsiehee.usc.edu/viterbi-lecture/
Webcast: https://bluejeans.com/401381224/More Information: 20180412 Tse Flyer.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
WebCast Link: https://bluejeans.com/401381224/
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
Event Link: https://minghsiehee.usc.edu/viterbi-lecture/
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Munushian Keynote Speaker - Dr. William Phillips - Nobel Laureate, Physics 1997, Friday, April 13th at 2pm in GER 124 Auditorium
Fri, Apr 13, 2018 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. William Phillips, Joint Quantum Institute, National Institute of Standards and Technology and University of Maryland
Talk Title: Quantum Information: a scientific and technological revolution for the 21st century
Abstract: Two of the great scientific and technical revolutions of the 20th century were the discovery of the quantum nature of the submicroscopic world, and the advent of information science and engineering. Both of these have had a profound effect not only on our daily lives but on our worldview. Now, at the beginning
of the 21st century, we see a marriage of quantum mechanics and information science in a new revolution: quantum information. Quantum computation and quantum communication are two aspects of this revolution.
The first is highly speculative: a new paradigm more different from today's digital computers than those computers are from the ancient abacus. The second is already a reality, providing information transmission whose security is guaranteed by the laws of physics. The JQI/NIST Laser Cooling and Trapping Group is studying the use of single, ultracold atoms as quantum bits, or qubits, for quantum information processing.
Biography: William D. Phillips was born in 1948, in Wilkes-Barre PA, and attended public primary and secondary schools in Pennsylvania. He received a B.S. in
Physics from Juniata College in 1970 and a Ph.D. from MIT in 1976. After two years as a Chaim Weizmann postdoctoral fellow at MIT, he joined the staff of the
National Institute of Standards and Technology (then the National Bureau of Standards) in 1978. He is currently leader of the Laser Cooling and Trapping Group in the Quantum Measurement Division of NIST's Physical Measurement Laboratory, and a Distinguished University Professor at the University of Maryland. He is a Fellow of the Joint Quantum Institute, a cooperative research organization of NIST and the University of Maryland that is devoted to the study of quantum coherent phenomena. At the JQI he is the co-director of an NSF-funded Physics Frontier Center focusing on quantum phenomena that span different subfields of physics.
The research group led by Dr. Phillips at NIST has been responsible for developing some of the main techniques now used for laser-cooling and cold-atom experiments in laboratories around the world, including the deceleration of atomic beams, magnetic trapping of atoms, the storage and manipulation of cold atoms with optical lattices, and the coherent manipulation of Bose-Einstein condensates. In 1988 the NIST group discovered that laser cooling could reach temperatures much lower than had been predicted by theory, a result that led to a new understanding of laser cooling and contributed to many of the subsequent developments in cold atomic gases. Early achievements included reaching laser-cooling temperatures within a millionth of a degree of Absolute Zero. Today, the group pursues research in laser cooling and trapping; Bose-Einstein condensation; atom optics; collisions of cold atoms; quantum information processing; cold atoms in optical lattices; production and transmission of non-classical light; and the study of cold-atom analogs to condensed matter systems. Phillips and colleagues demonstrated the first "atomic fountain" clock as proposed by Zacharias. Such clocks, as realized in other laboratories, have become the primary time standards for world timekeeping.
Dr. Phillips is a fellow of the American Physical Society and the American Academy of Arts and Sciences. He is a Fellow and Honorary Member of the Optical Society of America, a member of the National Academy of Sciences and the Pontifical Academy of Sciences, and a corresponding member of the Mexican Academy of Sciences. He is the recipient of the Gold Medal of the U. S. Department of Commerce (1993), the Michelson Medal of the Franklin Institute (1996), the Schawlow Prize of the American Physical Society (1998), and the Service to America Medal, Career Achievement Award 2006. In 1997, Dr. Phillips shared the Nobel Prize in Physics "for development of methods to cool and trap atoms with laser light."
Host: EE-Electrophysics
More Info: minghsiehee.usc.edu/about/lectures
Location: Ethel Percy Andrus Gerontology Center (GER) - 124
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
Event Link: minghsiehee.usc.edu/about/lectures