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Conferences, Lectures, & Seminars
Events for November
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Two New Approaches to Massive MIMO
Fri, Nov 01, 2013 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Ralf Mueller, FAU Erlangen-Nuremberg
Talk Title: Two New Approaches to Massive MIMO
Abstract: Massive MIMO systems are promising for solving the wireless bottleneck. Still some fundamental issues in massive MIMO are open. In this talk two of them are addressed: 1) The channel estimation problem which is often referred to as "pilot contamination". 2) The cost scaling problem which arises from the massive use of analog hardware. Concerning 1), a system design based on power-controlled handover and non-linear channel estimation is proposed. In particular, the signal subspaces occupied by intercell and intracell users are blindly separated by means of singular value decomposition. Concerning 2), a new hardware structure to generate RF signals is proposed. This structure avoids mixers and the need for linear power amplifiers. It consists of a single RF oscillator common to all antenna elements that is driving varying imaginary impedances and makes use of the law of large numbers for impedance matching.
Biography: Prof. Müller was born in Schwabach, Germany, 1970. He received the Dipl.-Ing. and Dr.-Ing. degree with distinction from the Friedrich-Alexander-University (FAU) Erlangen-Nuremberg in 1996 and 1999, respectively. From 2000 to 2004, he directed a research group at Vienna Telecommunications Research Center in Vienna, Austria and taught as an adjunct professor at Vienna University of Technology. In 2005, he was appointment full professor at the Department of Electronics and Telecommunications at the Norwegian University of Science and Technology in Trondheim, Norway. In 2013, he joined the Institute for Digital Communications at FAU Erlangen-Nuremberg in Erlangen, Germany. He held visiting appointments at Princeton University, US, Institute Eurecom, France, University of Melbourne, Australia, University of Oulu, Finland, National University of Singapore, Babes-Bolyai University, Cluj-Napoca, Romania, Kyoto University, Japan, FAU Erlangen-Nuremberg, Germany, and Munich University of Technology.
Prof. Müller received the Leonard G. Abraham Prize (jointly with Sergio Verdú) for the paper "Design and analysis of low-complexity interference mitigation on vector channels'' from the IEEE Communications Society. He was presented awards for his dissertation "Power and bandwidth efficiency of multiuser systems with random spreading'' by the Vodafone Foundation for Mobile Communications and the German Information Technology Society (ITG). Moreover, he received the ITG award for the paper "A random matrix model for communication via antenna arrays,'' as well as the Philipp-Reis Award (jointly with Robert Fischer). Prof. Müller served as an associate editor for the IEEE Transactions on Information Theory from 2003 to 2006
Host: Giuseppe Caire, caire@usc.edu, EEB 540, x04683
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. -
Integrated Systems Seminar Series
Fri, Nov 01, 2013 @ 03:30 PM - 05:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Prof. Harish Krishnaswamy, Columbia University
Talk Title: Power Generation in CMOS from RF to THz: A Spectrum of Challenges and Opportunities
Series: Integrated Systems Seminar Series
Abstract: Technology scaling has enabled CMOS to serve as a platform for the implementation of a wide range of wireless systems operating from radio frequencies to terahertz. However, while we have seen steady (actually, somewhat slowing) increases in speed with technology scaling, this has been accompanied by the inevitable shrinking of supply and breakdown voltages. Consequently, power generation in CMOS is plagued by fundamental trade-offs between output power, efficiency, fidelity and operating frequency. The RF, millimeter-wave and terahertz frequency ranges represent different points in this multi-dimensional trade-off, but each is faced with fundamental challenges dictated by application requirements.
mmWave power amplifiers have traditionally been limited to output power levels that are lower than 100mW and efficiencies lower than 20% due to the need to use scaled technologies with low supply voltages of around 1V. In this presentation, I will describe techniques developed at Columbia University, including device stacking, switch-mode operation at mmWave and low-loss on-chip power combining, that have enabled the first watt-class mmWave PA in CMOS.
At RF frequencies, speed can be traded-off for output power and consequently, watt-level output power is relatively straightforward. However, precision and signal fidelity, manifested as out-of-band emissions, are fundamental challenges, particularly for reconfigurable radios with reduced front-end filtering. This presentation will cover techniques recently developed at Columbia for receiver-band noise filtering in watt-level "digital PAs" and active cancellation of transmitter leakage and noise in reconfigurable receivers. These techniques enable frequency-division-duplexing in reconfigurable radios with relaxed transmitter-receiver isolation.
Finally, terahertz frequencies lie beyond the maximum operating frequencies of today's CMOS devices. I will briefly touch upon techniques that leverage device non-linearity to enable terahertz signal generation in CMOS in the milliwatt power envelope.
Biography: Harish Krishnaswamy received the B.Tech. degree in Electrical Engineering from the Indian Institute of Technology-Madras, India, in 2001, and the M.S. and Ph.D. degrees in Electrical Engineering from the University of Southern California (USC) in 2003 and 2009, respectively. He joined the EE department of Columbia University as an Assistant Professor in 2009. His research group at Columbia, funded by various federal agencies, including NSF and DARPA, and industry, focuses on various topics related to devices, circuits and systems for wireless communication, radar, imaging and sensing in the RF, millimeter-wave and terahertz frequency ranges. He received the IEEE International Solid State Circuits Conference (ISSCC) Lewis Winner Award for Outstanding Paper in 2007. He also received the Best Thesis in Experimental Research Award from the USC Viterbi School of Engineering in 2009, and the DARPA Young Faculty Award in 2011
Host: Hossien Hashemi, Mike Chen, Mahta Moghaddam, Kunal Datta
More Info: http://mhi.usc.edu/activities/integrated-systems/
More Information: Harish Krishnaswamy_Flyer.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 248
Audiences: Everyone Is Invited
Contact: Danielle Hamra
Event Link: http://mhi.usc.edu/activities/integrated-systems/
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Multimodal Neuroimaging, Analysis, and Modeling in Traumatic Brain Injury (TBI)
Mon, Nov 04, 2013 @ 10:30 AM - 11:30 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. John D. Van Horn, Department of Neurology/Keck School of Medicine of USC
Talk Title: Multimodal Neuroimaging, Analysis, and Modeling in Traumatic Brain Injury (TBI)
Abstract: The increasing interest in combining neuroimaging modalities to study brain structure, function and circuitry has brought about an appreciable challenge to image processing experts from the standpoint of inferring clinically valuable information based on enormous amounts of high-dimensionality imaging data. This challenge is particularly serious when attempting to quantify brain changes due to traumatic brain injury (TBI), a condition whose heterogeneity precludes the use of standard image processing algorithms for tissue segmentation, brain morphometry, population atlasing and neuroinformatics. Current efforts by translational researchers to formulate patient-tailored rehabilitation protocols for TBI must be complemented by critical input from neuroinformaticians, signal processing, and image analysis experts to develop next-generation image analysis methods for brain trauma. Because TBI-related deficits are predicated upon individual brain circuitry profiles, such methods must be robust enough to accommodate the heterogeneity and wide variety of structural deformation and degeneration patterns encountered in this condition. In this presentation, I will outline our recent computational and analytic efforts toward developing state-of-the-art neuroimaging analysis protocols and informatics approaches for characterizing brain injury longitudinally at the structural, functional, and connectomic levels. To improve on existing abilities to capture injury-related changes to the brain, we have combined multimodal magnetic resonance imaging (MRI), diffusion tensor imaging (DTI) and electroencephalography (EEG) with network theory, geometric modeling and inverse localization methods in the context of a sophisticated neuroimaging analysis approach. This has allowed us to longitudinally map TBI location, extent, and change over time. Further progress in this field depends critically upon input from the engineering and computer science communities to develop algorithms for segmentation, morphometry and atlasing which can handle the large structural brain deformations encountered in neurotrauma. Such contributions could result in substantial translational benefit to neurosurgeons, neurologists and psychiatrists who are interested in using neuroimaging to monitor brain injury evolution and for clinical intervention. Thus, despite substantial progress on quantifying TBI-related brain changes, considerable input is still needed from image processing, visualization and informatics experts to address the difficulties of this epidemiologically prominent field.
Biography: Dr. Van Horn is a recent addition to the USC faculty, having held prior positions at the National Institutes of Health, Dartmouth College, and UCLA. He received his Ph.D. from Department of Psychology at the University of London and hold a master's degree in engineering from the University of Maryland College Park. He explores the neurophysiology of the human brain using in vivo neuroimaging techniques, e.g. functional MRI, diffusion tensor imaging, and its relations to other biological systems. Areas of interest in neuroimaging include multimodal MRI, connectomics, characterizing the effects of neurotrauma, visuo-spatial task performance and motor learning. He has also examined the use of pharmacological manipulations as probes of cognitive and physiological networks during fMRI. He is also known for his contributions to neuroinformatics: mathematical modeling, experimental design, statistical, quantitative methods, data visualization, and the sociological and technical issues of neuroscientific data sharing, as well as neuroimaging data base and data mining. Presently, Dr. Van Horn is tenured faculty in the Department of Neurology at the Keck School of Medicine of USC and a principle member of the Institute for Neuroimaging and Informatics (INI).
Host: Dr. Sandeep Gupta, sandeep@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
New Neuroimaging Approaches for Understanding and Predicting Neurological Disease
Wed, Nov 06, 2013 @ 10:30 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Arthur W. Toga, University of Southern California
Talk Title: New Neuroimaging Approaches for Understanding and Predicting Neurological Disease
Abstract: The complexity of neurodegenerative diseases often requires the collection of numerous data types from multiple modalities. These can be genetic, imaging, clinical and biosample data. In combination, they can provide biomarkers critical to chart the progression of the disease and to measure the efficacy of therapeutic intervention. The difficulties lie in how can these diverse data from different subjects, collected across multiple laboratories on a wide range of instruments using non-identical protocols be aggregated and mined to discover meaningful patterns.
Mapping the human brain, and the brains of other species, has long been hampered by the fact that there is substantial variance in both the structure and function of this organ among individuals within a species. Previous brain atlases have relied on information from, at best, a few samples to draw conclusions. These limitations and the lack of quantification for the variance in brain structure and function have limited the pace and accuracy of research in the field of neuroscience. There are numerous probabilistic atlases that describe specific subpopulations, measure their variability and characterize the structural differences between them. Utilizing data from structural, functional, diffusion MRI, along with genome-wide association studies (GWAS) and clinical measures, we have built atlases with defined coordinate systems creating a framework for mapping and relating diverse data across studies. This talk describes the development and application of theoretical framework and computational tools for the construction of probabilistic atlases of large numbers of individuals in a population. These approaches are useful in understanding multidimensional data and their relationships over time.
A specific and important example of mapping multimodal data is the study of Alzheimerââ¬â¢s. The dynamic changes that occur in brain structure and function throughout life make the study of degenerative disorders of the aged difficult. The Alzheimerââ¬â¢s Disease Neuroimaging Initiative (ADNI) is a large national consortia established to collect, longitudinally, distributed and well described cohorts of age matched normals, mci's and Alzheimerââ¬â¢s patients. It results from the abnormal accumulation of misfolded amyloid and tau proteins in neurons and the extracellular space, ultimately leading to cell death and progressive cognitive decline. The consequences of this insult can be seen using a variety of imaging and other data analyzed from the ADNI database.
Essential elements in performing this type of population based research are the informatics infrastructure to assemble, describe, disseminate and mine data collections along with computational resources necessary for large scale processing of big data such as whole genome sequence data and imaging data. This talk also describes the methods we have employed to address these challenges.
Biography: Arthur W. Toga is a recent recruit to USC. Previously a Distinguished Professor of Neurology and University Professor at the University of California at Los Angeles (UCLA), he has been appointed as Provost Professor, Departments of Ophthalmology, Neurology, Psychiatry and the Behavioral Sciences, Radiology and Engineering. He is Director, USC Institute of Neuroimaging and Informatics and Director, Laboratory of Neuro Imaging (LONI) at USC. His research is focused on neuroimaging, informatics, mapping brain structure and function, and brain atlasing. He has developed multimodal imaging and data aggregation strategies and applied them in a variety of neurological diseases and psychiatric disorders. His work in informatics includes the development and implementation of some of the largest and most widely used databases and data mining tools linking disparate data from genetics, imaging, clinical and behavior, supporting global efforts in Alzheimerââ¬â¢s disease, Huntingtonââ¬â¢s and Parkinsonââ¬â¢s disease. He was trained in neuroscience and computer science and has written more than 700 papers, chapters and abstracts, including eight books. The 100 plus members of Laboratory of Neuro Imaging include graduate students from computer science, biostatistics and neuroscience. It is funded with grants from the National Institutes of Health grants as well as industry partners. He has received numerous awards and honors in computer science, graphics and neuroscience. He is the founding Editor-in-Chief of the journal NeuroImage and holds the chairmanship of numerous committees at NIH and a variety of international task forces.
Host: Hosted by Prof. Alexander Sawchuk
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
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. -
Learning and Coordination In Social Networks
Thu, Nov 07, 2013 @ 01:30 PM - 02:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Ali Jadbabaie, University of Pennsylvania
Talk Title: Learning and Coordination In Social Networks
Abstract: In the first part of this talk we examine how the structure of a social network and the quality of information available to different agents affects social learning and information aggregation. To this end, we study a variant of the seminal model of DeGroot, according to which agents linearly combine their personal experiences with the views of their neighbors. We show that the rate of learning has a simple analytical characterization in terms of the relative entropy of agents' signal structures and their eigenvector centralities. Our characterization establishes that the way information is dispersed throughout the social network has non-trivial implications for the rate of learning. In particular, we show that when the informativeness of different agents' signal structures are comparable, positive assortative matching of signal qualities and agent centralities maximizes the rate of learning. On the other hand, if information structures are such that each individual possesses some information crucial for learning, and the information endowments are not comparable, then the rate of learning is higher when agents with the best signals are located at the periphery of the network. Finally, we show that the extent of asymmetry in the structure of the social network plays a key role in the long-run dynamics of the beliefs.
In the second part, we introduce and analyze a novel model of opinion formation according to which agents not only seek to discover the truth but also have the tendency to act in conformity with the rest of the population. Such preferences for conformity are relevant in scenarios ranging from participation in popular movements to trading in stock market. We argue that agents who value conformity do not necessarily fully aggregate the dispersed information; nonetheless, we prove that examples of the failure of information aggregation are rare in a precise sense.
Biography: Ali Jadbabaie received his BS degree with High honors in Electrical Engineering (with a focus on Control Systems) from Sharif University of Technology, Tehran, Iran, in 1995. After a year of working as a control engineer, he moved to the US where he received a Masters degree in Electrical and Computer Engineering from the University of New Mexico, Albuquerque in 1997 and his Ph.D. degree in Control and Dynamical Systems from California Institute of Technology (Caltech) in 2001. From July 2001-July 2002 he was a postdoctoral scholar at the department of Electrical Engineering at Yale University. Since July 2002 he has been at the University of Pennsylvania, Philadelphia, PA, where he is currently The Alfred Fitler Moore Professor of Network Science in the department of Electrical and Systems Engineering with secondary appointments in departments of Computer & Information Sciences and Operations and Information Management (in the Wharton School of Management). He is a member of GRASP Laboratory and the director of the Raj and Neera Singh Program in Networked and Social Systems at Penn Engineering, a new interdisciplinary undergraduate degree program at Penn that blends Network Science, Operations Research, Economics, and Computer Science with Information and Decision Systems. He is a recipient of an NSF Career award, a Young Investigator award from the Office of Naval Research, the O. Hugo Schuck Best Paper award of the American Automatic Control Council, and the George S. Axelby Outstanding Paper Award of the IEEE Control Systems Society. His students have won best paper awards at the American Control Conference (ACC) and been award finalists at 3 IEEE CDC and ACC conferences. His research is broadly at the interface of systems and control theory with optimization and network science with focus on analysis, design and optimization of networked dynamical systems in a variety of applications including sensor networks, multi-robot formation control, opinion aggregation, and strategic interaction in social networks.
Host: Urbashi Mitra, ubli@usc.edu, EEB 536, x04667
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. -
EE Distinguished Lecturer Series
Thu, Nov 07, 2013 @ 03:30 PM - 04:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Luiz Barroso, Google Inc.
Abstract: As the field of warehouse-scale computing matures we continue to find new and interesting problems to solve. Some of the most interesting problems are the ones that are trivial to explain once identified, and yet remain very hard to solve. I’ll present three examples of such problems drawn from our experience building and operating large computing systems at Google.
Biography: Luiz Barroso is a Google Fellow, with technical interests that range from distributed systems software to the design of Google’s computing platform. While at Google he has co-authored some well-cited articles on warehouse-scale computing, energy proportionality and storage system reliability. He also co-wrote
The Datacenter as a Computer, the first textbook to describe the architecture of warehouse-scale computing systems, now in its 2nd edition.
Previously he was a member of the research staff at Digital Equipment Corporation and Compaq, where the group did some of the pioneering research on modern multi-core architectures. Some of those multi-core processors also use variants of the ring-based cache-coherency interconnects that were the subject of his doctoral research. As a graduate student he was one of the designers of the USC RPM, an early FPGA-based emulator for multiprocessor memory systems.
Barroso is a Fellow of the Association for Computing Machinery (ACM) and the American Association for the Advancement of Science. He was the program chair of ACM ISCA’09, a keynote speaker at FCRC’11, SIGMOD’10, ASPLOS’09, and a National Academy of Engineering Gilbreth Lectureship awardee in 2012. He is currently serving at the National Academies’ Computer Science and Telecommunications Board and has been a guest lecturer at Stanford and PUC-Rio, Brazil.
He holds B.S. and M.S. degrees in Electrical Engineering from the PontifÃcia Universidade Católica of Rio de Janeiro, and a Ph.D. in Computer Engineering from the University of Southern California.
Host: Dr. Michel Dubois
More Info: http://ee.usc.edu/news/dls/
Webcast: http://geromedia.usc.edu/Gerontology/Play/ef2f45debf48420d8ba985d18adfbf0f1dMore Information: 20131107 Barroso Print.pdf
Location: Ethel Percy Andrus Gerontology Center (GER) - Auditorium (GER 124)
WebCast Link: http://geromedia.usc.edu/Gerontology/Play/ef2f45debf48420d8ba985d18adfbf0f1d
Audiences: Everyone Is Invited
Contact: Estela Lopez
Event Link: http://ee.usc.edu/news/dls/
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. -
Analysis of Future Network Architectures
Fri, Nov 08, 2013 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Hamid Sadjadpour, UC Santa Cruz
Talk Title: Analysis of Future Network Architectures
Abstract: Future network architectures are being developed based on two main pillars. Software defined network (SDN) is the first effort to separate the network into two control and forwarding planes. The second main attempt is related to shifting from a host-centric paradigm to a content-centric approach. This new architecture is called information-centric network (ICN) where contents are accessed based on their names, and independently of the location of the hosts.
In this talk, we focus on information-theoretic analysis of these architectures. We show the throughput capacity of an information-centric network when the data cached in each node has a limited lifetime. The results show that with some fixed request and cache expiration rates, the network can have the maximum throughput order in cases of grid and random networks. Comparing these values with the corresponding throughput with no cache capability, we can actually quantify the asymptotic advantage of caching.
For SDN networks, we study some fundamental properties of the interface between control and forwarding planes, specifically in case of content routing. We evaluate the traffic between the two planes based on allowing a minimum level of acceptable distortion in the network state representation in the control plane. We apply our framework to content distribution, and show how we can compute the overhead of maintaining the location of content in the control plane. We identify scenarios where the cost of updating the control plane for content routing overwhelms the benefit of fetching the nearest copy. We also show how to minimize the cost of this overhead when associating costs to peering traffic and to internal traffic for operator-driven CDNs.
Biography: Hamid Sadjadpour received his B.S. and M.S. degrees in Electrical Engineering from Sharif University of Technology, Iran in 1986 and 1988 respectively. He received his Ph.D. from USC in 1996. After graduation, he worked at AT&T Shannon Lab. until 2001. In 2001, he joined University of California, Santa Cruz where he is currently a Professor in the Electrical Engineering department.
Host: Michael Neely, mjneely@usc.edu, EEB 520, x03505
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. -
Integrated Systems Seminar Series
Fri, Nov 08, 2013 @ 03:30 PM - 05:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Ghavam Shahidi, IBM Semiconductor
Talk Title: CMOS Technology Scaling for the Next 10 Years: Device-Technology Interaction and Scaling Value Proposition
Series: Integrated Systems Seminar Series
Abstract: Within the last few years, there has been speculation about the slow-down and even the end of Moore's Law. In this talk we review the benefit of the Moore's Law (with regard to low power and/or performance) over the last 20-30 years, and how the benefit has evolved over the last few years. It will be shown that there is a tight coupling between the choice of transistor and the node-to-node product benefit (using products from Intel and IBM as benchmark). As we move to the 14 nm and beyond, we will discuss device challenges and trade-offs. We will argue that the CMOS technology scaling will continue through 10 nm, 7 nm, and beyond nodes for the next 10 years.
Biography: Ghavam Shahidi received his B.S., M.S., and Ph.D. Degrees, all in electrical engineering, from MIT. In 1989 he joined the IBM Thomas J. Watson Research Center, where he initiated the SOI development program in IBM Research. The work ultimately resulted the first mainstream use of SOI. Ghavam Shahidi was the Director of High-Performance Logic Development in IBM Microelectronics until 2003. He is currently the Director of Silicon Technology in IBM Research Division and an IBM Fellow. His work is focused on 10 nm and beyond.
Host: Hossien Hashemi, Mike Chen, Mahta Moghaddam, Kunal Datta
More Info: http://mhi.usc.edu/activities/integrated-systems/
More Information: Ghavam Shahidi_Flyer.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 248
Audiences: Everyone Is Invited
Contact: Danielle Hamra
Event Link: http://mhi.usc.edu/activities/integrated-systems/
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Multimodal Brain Image Analysis for the Computational Mapping of Neuroanatomy
Mon, Nov 11, 2013 @ 10:30 AM - 11:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Yonggang Shi, Department of Neurology/Keck School of Medicine of USC
Talk Title: Multimodal Brain Image Analysis for the Computational Mapping of Neuroanatomy
Abstract: In this talk, I will present our recent work on the automated analysis of multimodal MR images for large scale brain mapping. I will first present a suite of novel algorithms for mapping brain structures using intrinsic geometry. The key idea in our method is the use of Laplace-Beltrami (LB) eigenfunctions for modeling brain shapes, such as hippocampus and cortex. These tools have the advantage of being invariant to pose and scale variances, and robust to deformations from development and pathology. Using the LB eigenfunctions and topology-preserving evolution, we have developed a robust approach for surface reconstruction from segmented masks. This method can remove outliers while accurately retaining volume information. For the challenging problem of cortical surface reconstruction, we have developed a unified approach for the joint correction of geometric and topological outliers with the Reeb graph of LB eigenfunctions. By using the LB embeddings of surfaces, we have developed a novel and general approach for surface mapping via the optimization of their conformal metrics. Based on these cutting-edge algorithms for image and shape analysis, completely automated workflows have been created for the large scale analysis of brain morphometry. In our current research, these intrinsic modeling techniques are being extended to multimodal image analysis for the more accurate and robust mapping of brain structure and function. Using the reconstructed cortical surfaces, we have developed more accurate ways of normalizing cerebral blood perfusion (CBF) images with cortical thickness and area, and successfully applied them to map sex differences in brain development. For the analysis of brain connectivity, we developed a novel algorithm for fiber orientation distribution (FOD) reconstruction that can be applied to diffusion imaging data collected from a wide range of acquisition schemes. With the help of FODs and intrinsic analysis, we are able to automatically extract fiber bundles with significantly improved details and robustness using the state-of-the-art data from the Human Connectome Project.
Biography: Dr. Yonggang Shi received his Bachelor and Master degree in Electrical Engineering from the Southeast University of China in 1996 and 1999, respectively. He received his Ph.D. in Electrical Engineering from Boston University in 2005. From 2005 to 2009, he was a PostDoctoral fellow at the Laboratory of Neuro Imaging (LONI) at UCLA. He was promoted to Assistant Professor at LONI in 2009. In July 2013, Dr. Shi was recruited to USC as a tenure-track Assistant Professor of Neurology. He joins USC along with other faculty members that previously had formed the Laboratory of Neuro Imaging (LONI) at UCLA to found the newly established Institute for Neuroimaging and Informatics (INI). Dr. Shi was a winner of student paper competition at the 2005 ICASSP for his work on a fast level set algorithm. He also won the Best Paper Award at the 2008 MMBIA for his work on using Reeb graphs of LB eigenfunctions to construct shape skeletons.
Host: Dr. Sandeep Gupta, sandeep@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
In Search for the "Perfect" Preclinical PET System
Tue, Nov 12, 2013 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Arion Chatziioannou, PhD , University of California, Los Angeles.
Talk Title: In Search for the "Perfect" Preclinical PET System
Series: Medical Imaging Seminar Series
Biography: Dr. Hadjioannou has a background in Biomedical Imaging Physics, with specific training in molecular imaging. As a post-doctoral fellow, he worked with Dr. Cherry towards the development of the original microPET preclinical imaging tomograph into a practical tool. That was followed by his appointment as the Director of the Preclinical Imaging Center at the UCLA Crump Institute for Molecular Imaging. In that position he helped mature the Imaging Center, and expand its capabilities to include microCT and optical bioluminescence imaging. In 2001, he joined the faculty ranks of the Department of Molecular and Medical Pharmacology at the David Geffen School of Medicine at UCLA. In 2008 he was appointed as the Associate Director of the Crump Institute for Molecular Imaging and Vice Chair of the Department of Molecular and Medical Pharmacology at UCLA. His research focuses on the development of instrumentation, methodologies and mathematical algorithms, for high resolution, quantitati ve in-v ivo preclinical imaging. He has been the PI and Co-PI in a number of NIH funded projects, that involve the development and use of these technologies, while a number of the technologies his lab has developed have been commercialized.
Host: Professor Richard Leahy
More Info: http://mhi.usc.edu/medical-imaging-seminar-series/
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Talyia Veal
Event Link: http://mhi.usc.edu/medical-imaging-seminar-series/
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. -
Signal Processing Methods for Diagnosing and Treating Neurological Disorders: A Focus on DBS
Wed, Nov 13, 2013 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Otis Smart, Emory University
Talk Title: Signal Processing Methods for Diagnosing and Treating Neurological Disorders: A Focus on DBS
Abstract: Worldwide, millions of patients with neurological disorders have an impaired quality of life, although in some cases successful therapeutic interventions can improve their life quality. Whether a patient has epilepsy, depression, malmovement, or another debilitating brain disease, neurologists and neurosurgeons rely on accurate diagnostic techniques and novel treatment modalities to effectively provide therapy. This talk presents bioengineering approaches, in particular signal processing of brain electrophysiology and electrical brain stimulation, which can contribute to these clinical needs in patient diagnosis and treatment.
Biography: Otis Smart received the B.S. degree in general science from Morehouse College in 2001 and the B.S., M.S. and Ph.D. degrees in electrical and computer engineering from the Georgia Institute of Technology in 2001, 2002 and 2007, respectively. Dr. Smart conducts interdisciplinary human-subjects research for projects that study epilepsy, depression, and movement disorders by applying bioengineering methods. His primary scientific interests focus on providing semi-automatic signal-processing algorithms that serve as reliable decision-support tools for physicians to better understand, diagnose, predict, and modulate pathological activity in patients with neurological disorders. He also applies signal processing analyses for basic science in vivo animal models and in vitro models of brain disorders. His interests also include developing biomedical devices for disease therapy and diagnosis. He currently is an NIH postdoctoral fellow at Emory University, supported by an NINDS postdoctoral career development award. He previously conducted research at the Emory Yerkes Primate Research Center, the Intelligent Control Systems Laboratory at Georgia Tech, the Psychophysiology Laboratory at NASA Ames Research Center, and Clemson University. He has also worked as a Radio-Frequency Engineer at Bellsouth Mobility.
Host: Panayiotis Georgiou
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Mary Francis
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. -
Adaptive, Parallel, and Asynchronous Stochastic Optimization Algorithms
Wed, Nov 13, 2013 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: John Duchi, University of California, Berkeley
Talk Title: Adaptive, Parallel, and Asynchronous Stochastic Optimization Algorithms
Abstract: In this talk, I will discuss some recent insights in stochastic optimization algorithms, focusing on new adaptive schemes that dynamically incorporate knowledge of the geometry of the data observed in earlier iterations to perform more informative gradient-based optimization. These ideas allow us to develop learning algorithms that are (in a sense) optimal for the data they actually receive. As a particular example of these schemes, we look at problems where the *data* is sparse, which is in a sense dual to the current understanding of high-dimensional statistical learning and optimization. We also show how these ideas can be leveraged in the design of parallel and asynchronous algorithms, providing experimental evidence to complement our theoretical results on several different learning and optimization tasks.
Biography: I am currently a PhD candidate in computer science at Berkeley, where I started in the fall of 2008. I work in the Statistical Artificial Intelligence Lab (SAIL) under the joint supervision of Mike Jordan and Martin Wainwright. I obtained my master's degree (MA) in statistics in Fall 2012. I was initially supported by an NDSEG fellowship, and until recently was supported by Facebook, who generously awarded me a Facebook Fellowship. Before this, I was an undergrad and a masters student at Stanford University working with Daphne Koller in her research group, DAGS. I also spend some time at Google Research (once upon a time I was also a software engineer there), where I had (and continue to have) the great fortune to work with Yoram Singer.
Host: Urbashi Mitra, ubli@usc.edu, EEB 536, x04667
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. -
"Low Power CMOS Design Past and Future", Bob Brodersen, HNB 100
Thu, Nov 14, 2013 @ 10:00 AM - 11:30 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Bob Brodersen, UC Berkeley
Talk Title: Low Power CMOS Design Past and Future
Abstract: Technology scaling provided a 100 times improvement in energy efficiency over the last 15-20 years. Unfortunately, while feature size scaling is continuing, scaling affecting energy efficiency will not continue these improvements. However, the demands for computation in mobile devices is accelerating, so even greater improvements will be required over the next 15-20 years. Techniques to obtain these improvements and their technology implications will be presented.
Biography: Robert W. Brodersen received a B.S. in both Electrical Engineering and Mathematics from California State Polytechnic University, Pomona, in 1966, and his M. S. and Ph.D. degrees in Electrical Engineering from MIT in 1968 and 1972, respectively. After spending three years with Texas Instruments in Dallas, he joined the faculty of the EECS Department at UC Berkeley in 1976; where he has pursued research in the areas of RF and digital wireless communications design, signal processing applications, and design methodologies. In 1994, he was the first holder of the John R. Whinnery Chair in Electrical Engineering and Computer Sciences. In 1998, he was instrumental in founding the Berkeley Wireless Research Center (BWRC), a consortium involving university researchers, industrial partners, and governmental agencies that is involved in all aspects of the design of highly integrated CMOS wireless systems. He retired in 2006 as Professor Emeritus but remains active at BWRC, where he is Co-Scientific Director, and at the Donald O. Pederson Center for Electronics Systems Design. His career includes significant contributions to the areas of low power design and wireless communications, including system-level, real-time prototyping, ultra-wideband radio systems, multiple-carrier multiple-antenna algorithms, microwave CMOS radio design, and the CAD tools necessary to support these activities.
Host: EE-Electrophysics
More Info: ee.usc.edu/news/munushian lecture series
Location: Hedco Neurosciences Building (HNB) - 100
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
Event Link: ee.usc.edu/news/munushian lecture series
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, Nov 15, 2013 @ 03:30 PM - 05:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Prof. Naveen Verma, Princeton University
Talk Title: Blending Electronics with the Physical World: sensing lots of signals from complex processes
Series: Integrated Systems Seminar Series
Abstract: Think about some of the physical systems with which we would like electronics to interact: physiological systems, high-value industrial equipment, critical infrastructureâ¦. These systems are complex, both in terms of the number of signals they present, and in terms of how those signals represent information. In this talk I will describe some of the hardware platforms we are pursuing to handle these complexities. By sensing âcomplex processes’, I am referring to an ability to make sense of embedded signals for which no tractable analytical models exist. Instead, we look at how sensor data can itself be used as a knowledge base, exploiting the data-acquisition capabilities of sensor networks towards the construction of high-quality data-driven models. Machine learning gives us powerful frameworks for data-driven analysis; the question is how to create very-low-power hardware to enable such frameworks within energy-constrained sensor devices. I will describe our work on low-power medical sensors for disease monitoring and harm detection. Sensing âlots of signals’ implies the ability to acquire embedded signals on a much larger scale than current technologies are equipped to handle. Large-area electronics is a technology that can enable the creation of large, flexible arrays of diverse transducers for sensing and energy harvesting. To build complete systems, however, substantial embedded computation, instrumentation, and power management capabilities are also required. We investigate scalable methods and architectures for combining large-area electronics with CMOS ICs to exploit the complementary strengths of both technologies towards translatable systems. I will describe our work towards smart infrastructure, using flexible sensing sheets to build complete, self-powered systems for high-resolution structural-health monitoring of bridges.
Biography: Naveen Verma received the B.A.Sc. degree in Electrical and Computer Engineering from the University of British Columbia, Vancouver, Canada in 2003 and the M.S. and Ph.D. degrees in Electrical Engineering from Massachusetts Institute of Technology in 2005 and 2009 respectively. Since July 2009 he has been an Assistant Professor of Electrical Engineering at Princeton University. His research focuses on advanced sensing systems, including low-voltage digital logic and SRAMs, low-noise analog instrumentation and data-conversion, large-area sensing arrays based on flexible electronics, and low-energy algorithms for embedded inference, especially for medical applications. Prof. Verma is recipient or co-recipient of the 2006 DAC/ISSCC Student Design Contest Award, 2008 ISSCC Jack Kilby Paper Award, 2012 Princeton Innovation Forum 1st Prize, 2012 Alfred Rheinstein Princeton Junior Faculty Award, 2013 NSF CAREER Award, and 2013 Intel Early Career Honor Award.
Host: Hossien Hashemi, Mike Chen, Mahta Moghaddam, Kunal Datta
More Info: http://mhi.usc.edu/activities/integrated-systems/
More Information: Naveen Verma_Flyer.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 248
Audiences: Everyone Is Invited
Contact: Danielle Hamra
Event Link: http://mhi.usc.edu/activities/integrated-systems/
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Simultaneous microPET/microMRI: Why's, What's and Applications
Tue, Nov 19, 2013 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Russell E. Jacobs, California Institute of Technology (CALTECH)
Talk Title: Simultaneous microPET/microMRI: Why's, What's and Applications
Series: Medical Imaging Seminar Series
Abstract: Positron Emission Tomography (PET) and Magnetic Resonance Imaging (MRI) are used extensively in both the research and clinical settings. In this project we combine them in a single instrument that will simultaneously record data in both imaging modalities. his system is dedicated to the study of small animal model systems at the highest spatial and temporal resolutions attainable. We have built a high resolution, relatively high sensitivity multi-slice mPET scanner integrated within a customized 7T/30cm small animal MR system that simultaneously records MR and PET images. In this talk I will briefly introduce the PET and MR imaging methodologies, discuss the rational for combining them in a single instrument, and present some results in oncology, multiple sclerosis, & vascular disease. Briefly, simultaneous mPET/mMRI recordings provide important correlations not available from temporally and spatially separate scans. The melded system provides high resolution anatomical reference systems for mPET studies. The 'in register' mMR images can be used to compute scatter and attenuation in the mPET images and to estimate partial volume errors in the PET scans, thus aiding quantification of the PET signal. This system will open up a number of opportunities not possible with current independent technologies. Among them are:
- Time correlated mPET and MR spectroscopy studies of drug distributions; cardiac, brain and tumor cell metabolism.
- Simultaneous fMRI and mPET neuroreceptor brain mapping studies in small animals.
- Validation of new MRI probes using their PET counterparts.
- Dual PET/MRI labels will allow for "zooming-in" the MRI data collection scheme to those regions of the specimen
containing the label, as well as providing for precise registration of the PET & MR images.
Biography: Russell E. Jacobs has more than 30 years experience in the theory, hardware/software development and application of high resolution preclinical MRI. Extensive history of supervising successful Post Doctoral fellows, graduate students, undergraduates, and technicians. Animal models understudy have included: embryonic development, multiple sclerosis, Alzheimer's Disease, cancer, and substance abuse. He is also heavily involved in several multimodal imaging efforts including contrast agent developments and implementation of a simultaneous dual PET/MRI scanner, and quantitative analysis of MR images using an array of computational warping and statistical parametric analyses.
Host: Professor Justin Haldar
More Info: http://mhi.usc.edu/medical-imaging-seminar-series/
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Talyia Veal
Event Link: http://mhi.usc.edu/medical-imaging-seminar-series/
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, Nov 20, 2013 @ 03:00 PM - 04:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Erik Winfree, Ph.D., California Institute of Technology
Abstract: Inspired by the information processing core of biological organisms and its ability to fabricate intricate machinery from the molecular scale up to the macroscopic scale, research in synthetic biology, molecular programming, and nucleic acid nanotechnology aims to create information-based chemical systems that carry out human-defined molecular programs that input, output, and manipulate molecules and molecular structures. For chemistry to become the next information technology substrate, we will need improved tools for designing, simulating, and analyzing complex molecular circuits and systems. Using DNA nanotechnology as a model system, I will discuss how programming languages can be devised for specifying molecular systems at a high level, how compilers can translate such specifications into concrete molecular implementations, how both high-level and low-level specifications can be simulated and verified according to behavioral logic and the underlying biophysics of molecular interactions, and how design and analysis methods can cope with the inherent stochasticity and uncertainties of molecular systems.
Biography: Erik Winfree is Professor of Computer Science, Computation and Neural Systems and Bioengineering at Caltech. He is the recipient of the Feynman Prize for Nanotechnology (2006), the NSF PECASE/CAREER Award (2001), the ONR Young Investigator Award (2001), a MacArthur Fellowship (2000), the Tulip prize in DNA Computing (2000), and MIT Technology Review’s first TR100 list of “top young innovators” (1999). Prior to joining the faculty at Caltech in 1999, Winfree was a Lewis Thomas Postdoctoral Fellow in Molecular Biology at Princeton, and a Visiting Scientist at the MIT AI Lab. Winfree received a B.S. in Mathematics and Computer Science from the University of Chicago in 1991, and a Ph.D. in Computation and Neural Systems from Caltech in 1998.
Host: Dr. Alice Parker
More Info: http://ee.usc.edu/news/dls/
Webcast: http://geromedia.usc.edu/Gerontology/Play/04ad0f98461441e8acc0297fd2ddc5371dLocation: Ethel Percy Andrus Gerontology Center (GER) - Auditorium (GER 124)
WebCast Link: http://geromedia.usc.edu/Gerontology/Play/04ad0f98461441e8acc0297fd2ddc5371d
Audiences: Everyone Is Invited
Contact: Estela Lopez
Event Link: http://ee.usc.edu/news/dls/
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. -
Closing-the-loop with Cyber Physical Systems
Thu, Nov 21, 2013 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Rahul Mangharam, University of Pennsylvania
Talk Title: Closing-the-loop with Cyber Physical Systems
Abstract: Cyber-Physical Systems are the next generation of embedded systems with the tight integration of computing, communication and control of “messy” plants. I will describe our recent efforts in modeling for scheduling and control of closed-loop Cyber-Physical Systems across the domains of medical devices, energy-efficient buildings, wireless control networks and programmable automotive systems.
In medical devices: the design of bug-free and safe software is challenging, especially in complex implantable devices that control and actuate organs whose response is not fully understood. Safety recalls of pacemakers and implantable cardioverter defibrillators between 1990 and 2000 affected over 600,000 devices. Of these, 200,000 or 41%, were due to software issues that continue to increase in frequency. There is currently no formal methodology or open experimental platform to test and verify the correct operation of medical device software within the closed-loop context of the patient. I will describe our efforts to develop the foundations of formal modeling, synthesis and development of verified medical device software and systems from verified closed-loop models of the pacemaker and the heart (more details here.)
In buildings: heating, cooling and air quality control systems operate independently of each other and frequently result in temporally correlated energy demand surges. As peak power prices are 200-400 times that of the nominal rate, this uncoordinated activity is both expensive and operationally inefficient. While several approaches for load shifting and model predictive control have been proposed, we present an alternative approach to fine-grained coordination of energy demand by scheduling energy consuming control systems within a constrained peak power while ensuring custom climate environments are facilitated. This project includes scheduling of energy control systems, sensing-based reduced order modeling of buildings and tools for integrated modeling and controls for energy-efficient buildings.
Biography: Rahul Mangharam is the Stephen J Angello Chair and Assistant Professor in the Dept. of Electrical & Systems Engineering and Dept. of Computer & Information Science at the University of Pennsylvania. He directs the Real-Time and Embedded Systems Lab at Penn. His interests are in real-time scheduling algorithms for networked embedded systems with applications in automotive systems, medical devices and industrial control networks.
He received his Ph.D. in Electrical & Computer Engineering from Carnegie Mellon University where he also received his MS and BS in 2007, 2002 and 2000 respectively. In 2002, he was a member of technical staff in the Ultra-Wide Band Wireless Group at Intel Labs. He was an international scholar in the Wireless Systems Group at IMEC, Belgium in 2003. He has worked on ASIC chip design at Marconi Communications (1999) and Gigabit Ethernet at Apple Computer Inc. (2000). Rahul received the 2013 NSF CAREER Award, 2012 Intel Early Faculty Career Award and was selected by the National Academy of Engineering for the 2012 US Frontiers of Engineering.
Host: Paul Bogdan
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. -
Rapid MRI for Sleep Apnea and Speech Production Research
Tue, Nov 26, 2013 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Yoon Kim, University of Southern California
Talk Title: Rapid MRI for Sleep Apnea and Speech Production Research
Series: Medical Imaging Seminar Series
Abstract: The human upper airway serves important functions such as speech, deglutition, and respiration. Understanding the nature or disorder of the upper airway functions has been of great interest in speech scientists, linguists, otolaryngologists, sleep medicine physicians, etc. MRI is noninvasive and has provided spatio-temporal information on the shaping of the tongue, soft palate, lips, and posterior/lateral pharyngeal walls with high frame rate (~20 fps).
In this talk, I will introduce our technical developments for the two NIH R01 projects: 1) dynamics of vocal tract shaping and 2) phenotyping of sleep-disordered breathing in pediatric obesity using dynamic MRI. On rapid MRI of speech, the talk will be an overview of 1) speech MRI acquisition environment, 2) novel acquisition techniques in real-time 2D, high-resolution 3D, and dynamic 3D imaging, and 3) various applications of real-time speech MRI. On rapid MRI of sleep, the talk will focus on 1) our sleep MR imaging protocols, 2) upper airway compliance measurement during inspiratory loading and 3) demonstrations of airway narrowing/collapse patterns during natural sleep in overweight and obese adolescents with sleep-disordered breathing.
Biography: Yoon Kim received his PhD in Electrical Engineering from USC in 2010. He is a postdoctoral research associate at USC from 2011 to 2013, working in the Magnetic Resonance Engineering Lab directed by Prof. Krishna Nayak. His research focuses on MRI pulse sequence design and image reconstruction for upper airway imaging and cardiac imaging. He is a recipient of American Heart Association postdoctoral fellowship award.
Host: Professor Krishna Nayak
More Info: http://mhi.usc.edu/medical-imaging-seminar-series/
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Talyia Veal
Event Link: http://mhi.usc.edu/medical-imaging-seminar-series/
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.
