SUNMONTUEWEDTHUFRISAT
Conferences, Lectures, & Seminars
Events for October
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Integrated Systems Seminar Series
Fri, Oct 02, 2015 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Yurii Vlasov, IBM T. J. Watson Research Center
Talk Title: Applications of Integrated Photonics Technology -” from Optical Interconnects to Neurophotonics
Series: Integrated Systems Seminar
Abstract: I will give an overview of the IBM Silicon Nanophotonics project that I led for over a decade from its early scientific exploration stage to technology transfer and qualification in IBM microelectronics foundry fab. The technology is aimed at low-power cost-efficient optical interconnects for internet mega-datacenters and high-performance computer systems. Such a disruptive technology is a result of a decade of multidisciplinary exploration in materials science, fundamental optics that extended further into advanced device and system engineering. I will touch upon its historical development, technology differentiators, current status and a roadmap. Time permits, I will also review a new area of neuro-engineering and neuro-photonics that I started to be engaged lately and discuss how integrated optics can be applied to the advancement in the brain science.
Biography: Dr. Yurii Vlasov is a Principal Member of Research Staff and a Manager of the Department of Brain-Inspired Technologies at the IBM T.J.Watson Research Center. He has been recognized as the founder and long-term leader of the IBM Silicon Nanophotonics project. He led the project from its early fundamental research state in 2001-2007 to advanced technology development in 2008-2010. In 2011-2013 Dr. Vlasov led the company-wide effort on transitioning the IBM Silicon Nanophotonics Technology to commercial manufacturing aimed at cost-optimized low-power optical transceivers for mega-datacenters and supercomputers. Dr. Vlasov is a Fellow of the OSA, the APS, and the IEEE. He has published over 300 peer-reviewed papers, filed over 100 patents, and delivered over 100 invited, plenary and tutorial talks. He was awarded the IBM Corporate Award, "Best of IBM" Award, as well as was named, "Scientist of the Year" by the Scientific American Journal. Prior to IBM, Dr. Vlasov developed semiconductor nanophotonics at the NEC Research Institute in Princeton and at the Strasbourg IPCMS Institute in France. For over a decade, he was also a Research Scientist with the Ioffe Institute of Physics and Technology in St. Petersburg, Russia working on optics of nanostructured semiconductors. He received his MS from the University of St. Petersburg (1988) and PhD from the Ioffe Institute (1994), both in Physics. Being an Adjunct Professor at Columbia University's Department of Electrical Engineering Dr. Vlasov taught courses on microelectronics and photonics.
Host: Hosted by Prof. Hossein Hashemi, Prof. Mike Chen, and Prof. Mahta Moghaddam. Organized and hosted by SungWon Chung.
Location: 132
Audiences: Everyone Is Invited
Contact: Elise Herrera-Green
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. -
Integrated Systems Seminar Series
Fri, Oct 02, 2015 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Yurii Vlasov, IBM T.J. Watson Research Center
Talk Title: Applications of Integrated Photonics Technology - from Optical Interconnects to Neurophotonics
Abstract: I will give an overview of the IBM Silicon Nanophotonics project that I led for over a decade from its early scientific exploration stage to technology transfer and qualification in IBM microelectronics foundry fab. The technology is aimed at low-power cost-efficient optical interconnects for internet mega-datacenters and high-performance computer systems. Such a disruptive technology is a result of a decade of multidisciplinary exploration in materials science, fundamental optics that extended further into advanced device and system engineering. I will touch upon its historical development, technology differentiators, current status and a roadmap. Time permits, I will also review a new area of neuro-engineering and neuro-photonics that I started to be engaged lately and discuss how integrated optics can be applied to the advancement in the brain science.
Biography: Dr. Yurii Vlasov is a Principal Member of Research Staff and a Manager of the Department of Brain-Inspired Technologies at the IBM T.J.Watson Research Center. He has been recognized as the founder and long-term leader of the IBM Silicon Nanophotonics project. He led the project from its early fundamental research stage in 2001-2007 to advanced technology development in 2008-2010. In 2011-2013 Dr. Vlasov led the company-wide effort on transitioning the IBM Silicon Nanophotonics technology to commercial manufacturing aimed at cost-optimized low-power optical transceivers for mega-datacenters and supercomputers. Dr. Vlasov is a Fellow of the OSA, the APS, and the IEEE. He has published over 300 peer-reviewed papers, filed over 100 patents, and delivered over 100 invited, plenary and tutorial talks. He was awarded the IBM Corporate Award, "Best of IBM" Award, as well as was named "Scientist of the Year" by the Scientific American journal. Prior to IBM, Dr. Vlasov developed semiconductor nanophotonics at the NEC Research Institute in Princeton and at the Strasbourg IPCMS Institute in France. For over a decade, he was also a Research Scientist with the Ioffe Institute of Physics and Technology in St. Petersburg, Russia working on optics of nanostructured semiconductors. He received his MS from the University of St.Petersburg (1988) and PhD from the Ioffe Institute (1994), both in physics. Being an Adjunct Professor at Columbia University's Department of Electrical Engineering Dr. Vlasov taught courses on microelectronics and photonics.
Host: Prof. Hossein Hashemi, Prof. Mike Chen, and Prof. Mahta Moghaddam
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. -
Integrated Systems Seminar Series
Fri, Oct 09, 2015 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Eric Fogleman, Maxlinear
Talk Title: Full-Spectrum Capture Receivers in Home Gateways: Circuit and Architecture Challenges
Series: Integrated Systems Seminar
Abstract: Full-Spectrum Capture or Direct Sampling architectures have emerged as a power-efficient solution in systems where channel bonding or aggregation is the path to increased throughput. While the classic notion of a direct-sampling receiver promises the simplicity of "direct to bits" signal path and leverages efficient digital signal processing, there are many challenges to a practical implementation. This talk will use the example of a DOCSIS home gateway - a system where Full-Spectrum Capture is now the industry norm - to walk through the system-level requirements and how they impact the IC architecture and implementation.
Biography: Dr. Eric Fogleman is Senior Director of the RF and MIxed-Signal IC Design Group at MaxLinear in Carlsbad, CA. He has been with MaxLinear since 2006, working on four generations of cable front-end chips for DOCSIS set-top boxes, cable modems, and cable gateways. Prior to MaxLinear, he designed data converters and analog circuits for Analog Devices, Silicon Wave, and Broadcom. He received the M.S. and Ph.D. degrees from the University of California, San Diego where he developed signal processing techniques to enable high-resolution analog-to-digital conversion.
Host: Hosted by Prof. Hossein Hashemi, Prof. Mike Chen, and Prof. Mahta Moghaddam. Organized and hosted by SungWon Chung.
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Elise Herrera-Green
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Communications, Networks & Systems (CommNetS) Seminar
Fri, Oct 09, 2015 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Bruno Sinopoli, Carnegie Mellon University
Talk Title: Cyber-Physical Systems: Performance, Robustness and Security
Series: CommNetS
Abstract: Recent advances in sensing, communication and computing allow cost effective deployment in the physical world of large-scale networks of sensors and actuators, enabling fine grain monitoring and control of a multitude of physical systems and infrastructures. Such systems, called cyber-physical, lie at the intersection of control, communication and computing. The close interplay among these fields renders independent design of the control, communication, and computing subsystems a risky approach, as separation of concerns does not constitute a realistic assumption in real world scenarios. It is therefore imperative to derive new models and methodologies to allow analysis and design of robust and secure cyber-physical systems (CPS). In this talk I will give an overview of my research on the CPS security, while briefly mentioning other research threads related to indoor positioning systems and adaptive streaming over HTTP.
Biography: Bruno Sinopoli received the Dr. Eng. degree from the University of Padova in 1998 and his M.S. and Ph.D. in Electrical Engineering from the University of California at Berkeley, in 2003 and 2005 respectively. After a postdoctoral position at Stanford University, Dr. Sinopoli joined the faculty at Carnegie Mellon University where he is an associate professor in the Department of Electrical and Computer Engineering with courtesy appointments in Mechanical Engineering and in the Robotics Institute and co-director of the Smart Infrastructure Institute, a research center aimed at advancing innovation in the modeling analysis and design of smart infrastructure. Dr. Sinopoli was awarded the 2006 Eli Jury Award for outstanding research achievement in the areas of systems, communications, control and signal processing at U.C. Berkeley, the 2010 George Tallman Ladd Research Award from Carnegie Mellon University and the NSF Career award in 2010. His research interests include networked embedded control systems, distributed estimation and control with applications to wireless sensor-actuator networks and Cyber-physical systems security.
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. -
Communications, Networks & Systems (CommNetS) Seminar
Wed, Oct 14, 2015 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Sucha Supittayapornpong, USC
Talk Title: Stochastic Network Optimization: The Steps Toward Realization
Series: CommNetS
Abstract: Optimizing communication networks such as throughput maximization and power minimization can be viewed as solving a stochastic network optimization problem, which leads to a control algorithm. Generally, the algorithm assumes infinite buffer space and converges to an optimal operating point within O(epsilon^-2) iterations, where epsilon is the proximity to the optimal operating point. In this talk, two aspects of the stochastic network optimization are focused on as the steps toward realization of the technique in practice. In the first part, the control algorithm that can be implemented by using only finite buffer space is considered. Specifically, when each queue in a network has buffer size B, the algorithm achieves within O(e^-B) of the optimality while a delay per queue is O(B) and an average drop rate is bounded by O(e^-B). In the second part, convergence times of a class of algorithms derived from a stochastic network optimization problem with non-convex decision sets are investigated. We show that the algorithm consists of two phases: transient phase and steady-state phase. The transient time, length of the transient phase, is O(epsilon^-1) and O(epsilon^-1.5) under locally-polyhedral and locally-smooth assumptions respectively. Performing a time average of decisions in the steady-state phase leads to faster convergence times that are O(epsilon^-1) and O(epsilon^-1.5) under the aforementioned assumptions.
Biography: Sucha Supittayapornpong is a Ph.D. candidate at University of Southern California, supervised by professor Michael J. Neely. His research interests include stochastic network optimization, distributed algorithms, and convergence analysis, with applications in communication networks, software-defined networking, and machine learning. He completed his M.Eng from Asian Institute of Technology and his B.Eng. from Kasetsart University, Thailand.
Host: Dr. 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. -
Advanced Parallel Imaging for Brain MRI Acquisitions
Fri, Oct 16, 2015 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Kawin Setsompop, Ph.D., Center of Biomedical Imaging, Harvard Medical School
Talk Title: Advanced Parallel Imaging for Brain MRI Acquisitions
Series: Medical Imaging Seminar Series
Host: Justin Haldar
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Talyia White
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Integrated Systems Seminar Series
Fri, Oct 16, 2015 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Prof. Gert Cauwenberghs, University of California, San Diego
Talk Title: Neuromorphic Silicon Learning Machines
Series: Integrated Systems Seminar
Abstract: Learning and adaptation are key to natural and artificial intelligence in complex and variable environments. Advances in machine learning and system-on-chip very-large-scale-integration have led to the development of massively parallel silicon learning machines with pervasive real-time adaptive intelligence that begin to approach the efficacy, efficiency and resilience of biological neural systems. Implemented in subthreshold CMOS analog and adiabatic charge-mode mixed-signal VLSI, these learning systems-on-chips offer throughput reaching the PetaMACS (10^15 multiply accumulates per second) per Watt range, or less than a femtojoule of energy per synaptic operation, exceeding the nominal energy efficiency of synaptic transmission in the mammalian brain. I will highlight examples of neuromorphic systems with applications in template-based pattern recognition, vision processing, and human-computer interfaces, and outline emerging scientific directions and engineering challenges in their large-scale deployment.
Biography: Dr. Gert Cauwenberghs is Professor of Bioengineering and Co-Director of the Institute for Neural Computation at UC San Diego. He received the Ph.D. in Electrical Engineering from Caltech in 1994, and was previously Professor of Electrical and Computer Engineering at Johns Hopkins University, and Visiting Professor of Brain and Cognitive Science at MIT. His research focuses on neuromorphic engineering, adaptive intelligent systems, neuron-silicon and brain-machine interfaces, and micropower biomedical instrumentation. He is a Fellow of the Institute of Electrical and Electronic Engineers (IEEE) and the American Institute for Medical and Biological Engineering (AIMBE), and was a Francqui Fellow of the Belgian American Educational Foundation. He previously received NSF CAREER, ONR Young Investigator Program and White House PECASE awards. He served IEEE in a variety of roles including currently as Editor-in-Chief of the IEEE Transactions on Biomedical Circuits and Systems.
Host: Hosted by Prof. Hossein Hashemi, Prof. Mike Chen, and Prof. Mahta Moghaddam. Organized and hosted by SungWon Chung.
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Elise Herrera-Green
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. -
Understanding Brain Abnormalities In Neuropsychiatric Disorders
Mon, Oct 19, 2015 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Ravi Bansal, Ph.D., University of Southern California
Talk Title: Understanding Brain Abnormalities In Neuropsychiatric Disorders
Series: Medical Imaging Seminar Series
Abstract: We have developed sophisticated mathematical and statistical techniques of identifying and quantifying the abnormalities in the morphology of brain regions that are associated with various neuropsychiatric disorders. Applying these techniques to large dataset of patients with various neuropsychiatric disorders we showed that the spatial patterns of these abnormalities are unique across mental illnesses. We quantified the spatial patterns of these abnormalities and applied machine learning algorithms for diagnosing individual patients as having a neuropsychiatric disorder or not. Rigorous, split-half cross validation showed that individuals can be diagnosed with high sensitivity and specificity. However, understanding the biological bases of these abnormalities is important not only for the reproducibility and but also for assessing validity of the MRI derived brain measures: Only reproducible MRI measures would be valid representation brain abnormalities and can increase our understanding of the causal mechanics in disease and subsequent development of early and effective treatments for mental illnesses. I therefore present findings from several studies that show how these together enhance our understanding of the various neuroplastic brain mechanisms in individuals with ADHD, thereby providing strong support for the validity of the MRI-derived findings.
Biography: My primary research interest is in the design and development of algorithms for the automated analysis of medical images. In particular, I am interested in the automated shape analysis of brain regions delineated on high-resolution anatomical MR images, and its application to studying the neurodevelopment of psychiatric disorders. I have developed and validated numerous important methods for the detailed analysis of anatomical surfaces in the brain, including strategies for controlling false positive (Type I) errors that can plague the multiple statistical tests involved in such analyses. Additionally, I am conducting research on mathematical and statistical models for the analyses of diffusion tensor images, white matter fiber tracking and registration, detection of signal in functional magnetic resonance images, nonrigid warping and coregistraiton of magnetic resonance images, and correction of intensity non-uniformities.
Host: Professor Richard Leahy
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Talyia Veal
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Communications, Networks & Systems (CommNetS) Seminar
Wed, Oct 21, 2015 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Soheil Feizi, MIT
Talk Title: Learning (from) networks: fundamental limits, algorithms, and applications
Series: CommNetS
Abstract: Network models provide a unifying framework for understanding dependencies among variables in medical, biological, and other sciences. Networks can be used to reveal underlying data structures, infer functional modules, and facilitate experiment design. In practice, however, size, uncertainty and complexity of the underlying associations render these applications challenging.
In this talk, we illustrate the use of spectral, combinatorial, and statistical inference techniques in several significant network science problems. First, we consider the problem of network alignment where the goal is to find a bijective mapping between nodes of two networks to maximize their overlapping edges while minimizing mismatches. To solve this combinatorial problem, we present a new scalable spectral algorithm, and establish its efficiency theoretically and experimentally over several synthetic and real networks. Next, we introduce network maximal correlation (NMC) as an essential measure to capture nonlinear associations in networks. We characterize NMC using geometric properties of Hilbert spaces and illustrate its application in learning network topology when variables have unknown nonlinear dependencies. Finally, we discuss the problem of learning low dimensional structures (such as clusters) in large networks, where we introduce logistic Random Dot Product Graphs, a new class of networks which includes most stochastic block models as well as other low dimensional structures. Using this model, we propose a spectral network clustering algorithm that possesses robust performance under different clustering setups. In all of these problems, we examine underlying fundamental limits and present efficient algorithms for solving them. We also highlight applications of the proposed algorithms to data-driven problems such as functional and regulatory genomics of human diseases, and cancer.
Biography: Soheil Feizi is a PhD candidate at Massachusetts Institute of Technology (MIT), co-supervised by Prof. Muriel Médard and Prof. Manolis Kellis. His research interests include analysis of complex networks and the development of inference and learning methods based on Optimization, Information Theory, Machine Learning, Statistics, and Probability, with applications in Computational Biology, and beyond. He completed his B.Sc. at Sharif University of Technology, awarded as the best student of his class. He received the Jacobs Presidential Fellowship and EECS Great Educators Fellowship, both from MIT. He has been a finalist in the Qualcomm Innovation contest. He received an Ernst Guillemin Award for his Master of Science Thesis in the department of Electrical Engineering and Computer Science at MIT.
Host: Dr. Salman Avestimehr
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Annie Yu
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
EE DISTINGUISHED LECTURER SERIES
Wed, Oct 21, 2015 @ 03:30 PM - 04:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Naomi Ehrich Leonard, Edwin S. Wilsey Professor of Mechanical and Aerospace Engineering / Princeton University
Talk Title: On the Nonlinear Dynamics of Collective Decision-Making in Nature and Design
Series: Distinguished Lecturer Series
Abstract: The successful deployment of complex multi-agent systems requires well-designed, agent-level control strategies that guarantee system-level dynamics to be robust to disturbance and adaptive in the face of changes in the environment. In applications, such as mobile sensor networks, limitations on individual agents in sensing, communication, and computation create a further challenge. However, system-level dynamics that are both robust and adaptive are observed in animal groups, from bird flocks to fish schools, despite limitations on individual animals in sensing, communication, and computation. To better understand and leverage the parallels between networks in nature and design, a principled examination of collective dynamics is warranted. I will describe an analytical framework based on nonlinear dynamical systems theory for the realization of collective decision-making that allows for the rigorous study of the mechanisms of observed collective animal behavior together with the design of distributed strategies for collective dynamics with provable performance.
Biography: Naomi Ehrich Leonard is the Edwin S. Wilsey Professor of Mechanical and Aerospace Engineering and an associated faculty member of the Program in Applied and She received a John D. and Catherine T. MacArthur Foundation Fellowship in 2004, the UCSB Mohammed Dahleh Award in 2005, the Glenn L. Martin Medal from the University of Maryland in 2014, and the Nyquist Lecture Award from the ASME in 2014. She is a Fellow of the IEEE, ASME, SIAM, and IFAC. She received the B.S.E. degree in Mechanical Engineering from Princeton University in 1985 and the M.S. and Ph.D. degrees in Electrical Engineering from the University of Maryland in 1991 and 1994. From 1985 to 1989, she worked as an engineer in the electric power industry.
Host: Sandeep Gupta, Justin Haldar, Urbashi Mitra
Webcast: https://bluejeans.com/694216021Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
WebCast Link: https://bluejeans.com/694216021
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. -
Munushian Seminar, "Harnessing Disorder for Photonics" - Hui Cao
Fri, Oct 23, 2015 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Hui Cao, Department of Applied Physics, Yale University
Talk Title: Harnessing Disorder for Photonics
Abstract: For device applications disorder and scattering have long been considered annoying and detrimental features that were best avoided or minimized. In this talk, I will show that disorder and complexity can be harnessed for photonics application, in particular, to provide unique functionalities of photonic devices. We recently developed an on-chip random spectrometer that combines high resolution with small footprint. In addition, we incorporated disorder to a laser to reduce the spatial coherence for free-speckle full-field imaging.
Biography: Hui Cao is a Professor of Applied Physics and of Physics at Yale University, New Haven, Connecticut. She received her B.S. degree (1990) in Physics from Peking University, and her Ph.D. degree (1997) in Applied Physics from Stanford University. Her doctoral research was in the area of semiconductor microcavity quantum electrodynamics. Prior to joining the Yale faculty in 2008, Professor Cao was on the faculty of the Department of Physics and Astronomy at Northwestern University. Her technical interests and activities are in the areas of complex photonic materials and devices, nanophotonics, and biophotonics. She has co-authors one book and ten book-chapters, and has published more than 200 research papers in the area of random lasers, optical microcavities, photonic crystals, and structural coloration. She is the recipient of the NSF CAREER award, Packard Fellowship, Sloan Fellowship, Maria Goeppert-Mayer Award and Guggenheim Fellowship. She is also a fellow of the American Physical Society, a fellow of the Optical Society of America, and a member of Connecticut Academy of Science & Engineering.
Host: EE-Electrophysics
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Communications, Networks & Systems (CommNetS) Seminar
Wed, Oct 28, 2015 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Ayfer Ozgur, Stanford University
Talk Title: Energy Harvesting and Rechargeable Wireless Networks
Series: CommNetS
Abstract: Energy-harvesting and wireless power transfer are quickly becoming game-changing technologies for wireless systems. The promise of self-sustained perpetual operation opens exciting possibilities for a wide range of applications from smart homes and automated highways to in-body health monitoring.
However, energy harvesting also brings a fundamental shift in communication system design principles. In conventional systems, energy is a deterministic quantity continuously available to the transmitter and transmission is constrained only in terms of average power. In harvesting systems, energy generation can be slow, unpredictable and fluctuate significantly over time, and communication is constrained by the energy instantaneously available to the transmitter. This necessitates new principles for power control, communication and coding. In this talk, we investigate the information and communication-theoretic foundations for this new form of communication.
Biography: Ayfer Ozgur is an Assistant Professor in the Information Systems Laboratory at Stanford University since 2012. Before joining Stanford, she was a postdoctoral researcher and a Ph.D. student at EPFL, Switzerland. She received her Ph.D. degree from EPFL in 2009 and B.Sc. and M.Sc.degrees in electrical engineering and physics from Middle East Technical University, Turkey in 2001 and 2004 respectively. From 2001 to 2004, she worked as a hardware design engineer for the Defense Industries Research and Development Institute in Turkey. She received the EPFL Best Ph.D. Thesis Award (accross all areas) in 2010 and the NSFCAREER Award in 2013. Her research interests are in wireless and network communication, information and coding theory.
Host: Dr. Salman Avestimehr
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Annie Yu
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Computer Engineering Seminar
Fri, Oct 30, 2015 @ 10:30 AM - 11:30 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Jae-sun Seo, Arizona State University
Talk Title: Efficient Digital Hardware Design for Machine Learning and Neuromorphic Algorithms
Abstract: In recent years, machine learning algorithms (e.g. convolutional neural networks, deformable parts model) have been widespread across a broad range of image, video, speech, and biomedical applications. For similar applications, there also has been a surge of interest in neuromorphic computing and spiking neural networks (e.g. TrueNorth), which more closely follow biological nervous systems. In this talk, we present our exemplary research work on efficient digital hardware design for both machine learning and neuromorphic algorithms.
On the machine learning side, algorithms trained by offline back propagation works well on pre-defined datasets, but state-of-the-art algorithms are compute-/memory-intensive, making it difficult to perform low-power real-time classification. Our prototype designs in FPGA and ASIC frameworks are presented that improve the energy-efficiency (GOPS/W) by optimizing computation, memory, and communication for representative large-scale networks.
On the neuromorphic side, the classification accuracies on MNIST or ImageNet datasets has not yet reached those of machine learning counterparts, but we find it suitable for unsupervised continuous online learning applications (e.g. defense, robotics, biomedical) aiming low power consumption. Building up on earlier work on on-chip STDP (spike-timing dependent plasticity) learning for pattern recognition (45nm) and spiking clustering for deep-brain sensing (65nm), we propose a versatile neuromorphic processor that can support various STDP learning and inhibition rules with large fan-in/out per neuron. Preliminary implementation results and future research directions will be discussed.
Biography: Jae-sun Seo received his Ph.D. degree from the University of Michigan in 2010 in electrical engineering. From 2010 to 2013, he was with IBM T. J. Watson Research Center, where he worked on energy-efficient circuits for high-performance processors and neuromorphic chip design for the DARPA SyNAPSE project. In January 2014, he joined Arizona State University as an assistant professor in the School of ECEE. During the summer of 2015, he was a visiting faculty at Intel Circuit Research Labs. His research interests include efficient hardware design of learning algorithms and integrated power management. He received the IBM outstanding technical achievement award in 2012, and serves on the technical program committee for ISLPED.
Host: Prof. Massoud Pedram
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. -
Munushian Keynote Seminar - Dr. Shuji Nakamura, "Development of Blue InGaN LEDs and Future lighting"
Fri, Oct 30, 2015 @ 03:00 PM - 04:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Shuji Nakamura, UC Santa Barbara
Talk Title: Development of Blue InGaN LEDs and Future lighting
Abstract: The development of high brightness blue LEDs and blue laser diodes required many breakthroughs of GaN growth, p-type conductivity control, InGaN growth and device structures using InGaN/GaN double heterostructures. First, I will discuss the history and background story of the key scientific issues solved in order to realize high efficiency solid state lighting. The fundamental discovery of high quality p-type doping by removing hydrogen passivation, and the role of the InGaN layer in achieving high brightness blue LEDs and Laser Diodes will be described.
Next the speaker will talk about the GaN on GaN LEDs developed by Soraa. The peak wall-plug efficiency of the violet is 84%. There is an intrinsic problem of the LEDs that cannot be easily overcome. When we increase the current densities so high, a reduction in efficiency with increasing the current density is observed. This phenomena, referred to as efficiency droop, forces LED manufactures to operate LEDs at lower current densities (and hence reduced light output) than would be possible to prevent excess heating of the device. An alternative method to produce white light is by using a blue laser, as opposed to an LED, in combination with a phosphor. Above the lasing threshold, the carrier density is clamped at threshold, fixing its density. Increases in carrier density beyond the threshold density immediately contribute to stimulated emission, or lasing. Thus, the carrier density is maintained at the lower, threshold density, prohibiting it from reaching densities where the Auger recombination process becomes the dominant recombination process. Auger recombination, with the resulting efficiency droop, does not appreciably occur in blue laser diodes.
Biography: Shuji Nakamura was born on May 22, 1954 in Ehime, Japan. He obtained B.E., M.S., and Ph.D. degrees in Electrical Engineering from the University of Tokushima, Japan in 1977, 1979, and 1994, respectively. He joined Nichia Chemical Industries Ltd in 1979. In 1989, he started the research of blue LEDs using group-III nitride materials. In 1993 and 1995, he developed the first group-III nitride-based blue/green LEDs. He also developed the first group-III nitride-based violet laser diodes (LDs) in 1995. He is the 2014 Nobel Laureate in Physics for the invention of efficient blue light-emitting diodes which has enabled bright and energy-saving white light sources.
Since 2000, he has been a professor of Materials and Electrical & Computer Engineering at the University of California, Santa Barbara. He holds more than 200 US patents and over 300 Japanese patents. He has published over 550 papers in his field. Prof. Nakamura is the Research Director of the Solid State Lighting & Energy Electronics Center and The Cree Chair in Solid State Lighting & Displays. He co-founded Soraa, Inc. in 2008, which operates vertically integrated fabrication facilities in California's Silicon Valley and Santa Barbara.
Host: EE-Electrophysics
More Info: http://viterbi.usc.edu/news/events/keynote/munushian/
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
Event Link: http://viterbi.usc.edu/news/events/keynote/munushian/
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.
