SUNMONTUEWEDTHUFRISAT
Conferences, Lectures, & Seminars
Events for January
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EE Seminar
Thu, Jan 03, 2019 @ 10:00 AM - 11:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Anup Basu, PhD, Professor, University of Alberta
Talk Title: Perceptually Motivated Multimedia
Abstract: In this talk we will discuss how biological motivation can help develop better and more robust image processing and computer vision algorithms. More specifically we will outline multi-camera motion estimation, active camera calibration, foveated image/video/3D compression, and the role of spatially varying sensing in 3D perception and depth reconstruction. We will also try to draw similarities between these algorithms and biological processing and understanding of images. We will also briefly discuss some of the recent research in our lab in medical imaging, surgical planning and other application areas.
Biography: Anup Basu received his Ph.D. in CS from the University of Maryland, College Park, USA. He o/riginated the use of foveation for image, video, stereo and graphics communication in the early 1990s; an approach that is now widely used in industrial standards. He also developed the first robust (correspondence free) 3D motion estimation algorithm using multiple cameras, a robust (and the first correspondence free) active camera calibration method, a single camera panoramic stereo, and several new approaches merging foveation and stereo with application to 3D TV visualization and better depth estimation. His current research applications include 3D/4D Image Processing and Visualization especially for medical applications, Multimedia in Education and Games, and Wireless 3D Multimedia transmission. He has been a Professor in the CS Department at University of Alberta since July 1999. He has also been a Visiting Professor, at University of California, Riverside; Guest Professor, at Technical University of Austria, Graz; Director, Hewlett-Packard Imaging Systems Instructional Lab.; Visiting Prof. in INSA, Lyon and Telecomm Paris; and an NSERC-AITF Research Chair.
Host: Jay Kuo
More Information: Basu Seminar Announcement.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Gloria Halfacre
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Processing Data Where It Makes Sense In Modern Computing Systems: Enabling In-Memory Computation
Thu, Jan 10, 2019 @ 03:45 PM - 05:45 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Onur Mutlu, ETH Zurich, Carnegie Mellon University
Talk Title: Processing Data Where It Makes Sense In Modern Computing Systems: Enabling In-Memory Computation
Abstract: Today's systems are overwhelmingly designed to move data to computation. This design choice goes directly against at least three key trends in systems that cause performance, scalability and energy bottlenecks: 1) data access from memory is already a key bottleneck as applications become more data-intensive and memory bandwidth and energy do not scale well, 2) energy consumption is a key constraint in especially mobile and server systems, 3) data movement is very expensive in terms of bandwidth, energy and latency, much more so than computation. These trends are especially severely-felt in the data-intensive server and energy-constrained mobile systems of today.
At the same time, conventional memory technology is facing many scaling challenges in terms of reliability, energy, and performance. As a result, memory system architects are open to organizing memory in different ways and making it more intelligent, at the expense of slightly higher cost. The emergence of 3D-stacked memory plus logic as well as the adoption of error correcting codes inside the latest DRAM chips are an evidence of this trend.
In this talk, I will discuss some recent research that aims to practically enable computation close to data. After motivating trends in applications as well as technology, we will discuss at least two
promising directions: 1) performing massively-parallel bulk operations in memory by exploiting the analog operational properties of DRAM, with low-cost changes, 2) exploiting the logic layer in 3D-stacked memory technology in various ways to accelerate important data-intensive applications. In both approaches, we will discuss relevant cross-layer research, design, and adoption challenges in devices, architecture, systems, applications, and programming models. Our focus will be the development of in-memory processing designs that can be adopted in real computing platforms and real data-intensive applications, spanning machine learning, graph processing and genome analysis, at low cost. If time permits, we will also discuss and describe simulation and evaluation infrastructures that can enable exciting and forward-looking research in future memory systems, including Ramulator and SoftMC.
Biography: Onur Mutlu is a Professor of Computer Science at ETH Zurich. He is also a faculty member at Carnegie Mellon University, where he previously held Strecker Early Career Professorship. His current broader research interests are in computer architecture, systems, and bioinformatics. A variety of techniques he, along with his group and collaborators, has invented over the years have influenced industry and have been employed in commercial microprocessors and memory/storage systems. He obtained his PhD and MS in ECE from the University of Texas at Austin and BS degrees in Computer Engineering and Psychology from the University of Michigan, Ann Arbor. He started the Computer Architecture Group at Microsoft Research (2006-2009), and held various product and research positions at Intel Corporation, Advanced Micro Devices, VMware, and Google. He received the inaugural IEEE Computer Society Young Computer Architect Award, the inaugural Intel Early Career Faculty Award, US National Science Foundation CAREER Award, Carnegie Mellon University Ladd Research Award, faculty partnership awards from various companies, and a healthy number of best paper or "Top Pick" paper recognitions at various computer systems, architecture, and hardware security venues. He is an ACM Fellow "for contributions to computer architecture research,
especially in memory systems", IEEE Fellow for "contributions to computer architecture research and practice", and an elected member of the Academy of Europe (Academia Europaea). For more information, please see his webpage at https://people.inf.ethz.ch/omutlu/.
Host: Xuehai Qian, xuehai.qian@usc.edu
More Information: 19.01.10 Onur Mutlu_CENG Seminar.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Brienne Moore
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. -
Fall 2018 Joint CSC@USC/CommNetS-MHI Seminar Series
Mon, Jan 14, 2019 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dominique Duncan, University of Southern California
Talk Title: Analytic tools for identifying biomarkers of epileptogenesis after traumatic brain injury using multi-modal data and virtual reality to correct segmentation errors in MRI
Abstract: The first part of my talk focuses on identifying biomarkers that can predict epileptogenesis after traumatic brain injury (TBI). This project, The Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx), is a multi-site, international collaboration including a parallel study of humans and an animal model, collecting MRI, EEG, and blood samples. The development of epilepsy after TBI is a multifactorial process and crosses multiple modalities. Without a full understanding of the underlying biological effects, there are currently no cures for epilepsy. This study hopes to address both issues, calling upon data generated and collected at sites spread worldwide among different laboratories, clinical sites, in different formats, and across multicenter preclinical trials. Before these data can even be analyzed, a central platform is needed to standardize these data and provide tools for searching, viewing, annotating, and analyzing them. We have built a centralized data archive that will allow the broader research community to access these shared data in addition to analytic tools to identify and validate biomarkers of epileptogenesis in images and electrophysiology as well as in molecular, serological, and tissue studies.
The second part of this talk focuses on crowdsourcing manual validation of algorithmically-segmented brain volumes using virtual reality. One of our imaging workflow processes involves algorithmic segmentation of the scans into labeled anatomical regions using FreeSurfer software. Since this automation cannot yet achieve perfect accuracy, we are working on transforming the way this is accomplished using VR technology to deal with the volumes directly in 3D space, which has been shown to be more efficient and intuitive.
Biography: Dominique Duncan is an assistant professor of Neurology at the USC Stevens Neuroimaging and Informatics Institute in the Laboratory of Neuro Imaging (LONI). She began working at LONI in 2015 as a postdoctoral scholar with Dr. Arthur Toga. Dr. Duncan's background spans mathematics, engineering, and neuroscience. She double majored in Mathematics and Polish Literature as an undergraduate at the University of Chicago and minored in Computational Neuroscience. She earned her PhD in Electrical Engineering at Yale University. In her PhD thesis, she analyzed intracranial EEG data using nonlinear factor analysis to identify preseizure states of epilepsy patients. After graduation, she was a professor of Mathematics at Sichuan University in Chengdu, China for a summer program where she taught Calculus 2, Calculus 3, and Linear Algebra to undergraduate students. She then took a postdoctoral position in Neurology at the Stanford University School of Medicine as well as one in Mathematics at UC Davis, where she developed an algorithm based on diffusion maps to classify Alzheimer's patients using MRI. Her current projects include combining machine learning and crowdsourcing segmentation error corrections in neuroimaging data using virtual reality, developing analytic tools to identify biomarkers of epileptogenesis after traumatic brain injury, and building a multi-modal data repository for human invasive recordings.
Host: Mihailo Jovanovic, mihailo@usc.edu
More Info: http://csc.usc.edu/seminars/2019Spring/duncan.html
More Information: 19.01.14 Dominique Duncan CSCUSC Seminar.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Brienne Moore
Event Link: http://csc.usc.edu/seminars/2019Spring/duncan.html
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. -
Control-System Interactions in Cyber-Physical Infrastructures
Wed, Jan 16, 2019 @ 03:00 PM - 04:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Sandip Roy , School of Electrical Engineering and Computer Science at Washington State University
Talk Title: Control-System Interactions in Cyber-Physical Infrastructures
Series: Center for Cyber-Physical Systems and Internet of Things
Abstract: Cyber- technologies are enabling a new paradigm for control in modern infrastructure networks, centered around client-catered and mission-adaptive decision-making. While this new paradigm holds remarkable promise, it also brings forth fundamental new challenges in infrastructure controls engineering, including growing democratization of control authority, increasing vulnerability to cyber attacks and failures, dependence on ad hoc sensing, and concern about system-wide cascading events. In this talk, the new paradigm and attendant challenges in infrastructure-network control are illustrated in two very different application domains: deployment of new wide-area controls to damp oscillations in the bulk power grid, and management of emergent antibiotic-resistant emergent infections at multiple scales. Then, a research program for assessing and designing infrastructure controls is envisioned, which is based on understanding interactions among control systems in dynamical networks. Specifically, four directions of work are overviewed: 1) input-output (channel) analysis for dynamical networks, 2) control-channel interaction assessment, 3) channel-preserving model reduction, and 4) ad hoc sensing-based control. Preliminary theoretical results and contributions to several application domains, including the two motivating applications, are presented.
Biography: Sandip Roy is a Professor in the School of Electrical Engineering and Computer Science at Washington State University. His research is concerned with developing techniques for the estimation and control of network dynamics, and applying these techniques to support the wide-area management of cyber-physical infrastructures. This research has yielded algorithms and decision-support software that are being prototyped in the United States air traffic management system and the Western U.S. power grid. Recently, he has been also interested in developing network-controls techniques for epidemiological and neuroscience applications. The outcomes of the research are described in about 70 journal papers and 130 conference papers across multiple disciplines.
Host: Paul Bogdan
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. -
Stochastic Optimal Control – Overview and Recent Advancesces
Wed, Jan 23, 2019 @ 03:00 PM - 04:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Ioannis Exarchos , Department of Biomedical Informatics, Emory University
Talk Title: Stochastic Optimal Control -“ Overview and Recent Advances
Series: Center for Cyber-Physical Systems and Internet of Things
Abstract: Stochastic optimal control lies within the foundation of mathematical control theory ever since its inception. Its usefulness has been proven in a plethora of engineering applications, such as autonomous systems, robotics, neuroscience, and financial engineering, among others. Specifically, in robotics and autonomous systems, stochastic control has become one of the most successful approaches for planning and learning, as demonstrated by its effectiveness in many applications, such as control of ground and aerial vehicles, articulated mechanisms and manipulators, and humanoid robots. In computational neuroscience and human motor control, stochastic optimal control theory has been used in the process of modeling the underlying computational principles of the neural control of movement. Furthermore, in financial engineering, stochastic optimal control provides the main computational and analytical framework, with widespread application in portfolio management and stock market trading.
The aim of this talk is to provide an overview on model-based stochastic optimal control and highlight some recent advances in its field. We will briefly present some well-established methods (Differential Dynamic Programming, Path Integral Control), illustrating their differences in approach and restrictive conditions. Motivated by these restrictive conditions, we will then present a novel framework for stochastic optimal control that capitalizes on the innate relationship between certain nonlinear PDEs and Forward and Backward Stochastic Differential Equations (FBSDEs), that relaxes some of these conditions. The utility of the proposed method will be demonstrated on some examples of L2- and L1- optimal control, as well as differential games.
Biography: Ioannis Exarchos received his Diploma degree (graduating valedictorian) in Mechanical Engineering and Aeronautics from the University of Patras, Greece, in 2010. He also received an M.S. degree in Mathematics in 2015, as well as his M.S. and Ph.D. degrees in Aerospace Engineering in 2013 and 2017 respectively, all from the Georgia Institute of Technology. During his PhD studies, he was an Onassis Foundation fellowship scholar. His research interests include stochastic optimal control, machine learning applications in control and neuroscience, dynamical systems and system identification, as well as differential game theory. He is currently a postdoctoral fellow at the Department of Biomedical Informatics, Emory University.
Host: Paul Bogdan
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. -
Ming Hsieh Institute Visitor Program
Thu, Jan 24, 2019 @ 11:00 AM - 12:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: H. Vincent Poor, Michael Henry Strater University Professor of Electrical Engineering at Princeton University
Talk Title: Fundamentals for Low Latency Communications
Abstract: Information theory provides fundamental insights into communication system capabilities, and the classical theory of Shannon has guided development of such systems over many decades. However, the classical models are based on assumptions of infinite block-length codes and not address situations in which short block lengths are imposed by system design considerations.
Notably in this context, latency has become a critical design issue in emerging wireless networking paradigms, such as the Internet of Things and associated applications like autonomous driving, factory automation, etc. This situation has inspired the development of a finite-block-length information theory, with man new results coming in recent years. This talk will review these developments, including fundamental finite-block-length results for the basic models of network information theory. Age of Information, another approach to the fundamental study of latency, will also be discussed briefly.
Biography: H. Vincent Poor is the Michael Henry Strater Professor of Electrical Engineering at Princeton University. From 1977, and until joining the Princeton faculty in 1990, he was on the faculty of the University of Illinois. During 2006 - 2016, he served as Dean of Princeton's School of Engineering and Applied Science. He has also held visiting positions at several other universities, including most recently at Berkeley and Cambridge. Dr. Poor's research interests are in the areas of signal processing and information theory and their applications in wireless networks, energy systems and related fields. He is a member of the National Academy of Engineering and the National Academy of Sciences, and is a foreign member of the Chinese Academy of Sciences, the Royal Society, and other national and international academies. He received the IEEE Alexander Graham Bell Medal in 2017.
Host: MHI
Location: 132
Audiences: Everyone Is Invited
Contact: Benjamin Paul
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. -
EEG Characteristics of Major Depressive Disorder Patients with Suicidal Symptoms
Fri, Jan 25, 2019 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Lars Benschop, Ghent Experimental Psychiatry Ghent University Hospital in Belgium
Talk Title: EEG Characteristics of Major Depressive Disorder Patients with Suicidal Symptoms
Biography: Lars Benschop is a PhD candidate from the Ghent Experimental Psychiatry (GHEP) lab at the Ghent University hospital in Belgium. He received his Master's degree in experimental and biological psychology from the University of Ghent.
Lar's research focuses on identifying clinically relevant neural electrophysiological biomarkers in major depressive disorder (MDD) patients with a high risk of suicide. His first study applied a cluster-based permutation analysis on EEG spatial-frequency resting-state data to evaluate differences with respect to suicide risk.
Currently, Lars is designing a combined resting state and task-based study in which 90 MDD patients with varying suicide risk will be shown death and life-related concepts (words and pictures) while undergoing EEG. The aim is to replicate the findings of the first study while also expanding into the time-frequency domain to further our understanding of the suicidal brain. Additionally, Lars will be applying machine learning techniques with the goal of differentiating between MDDs with and without suicide risk.
Outside of his research interests, Lars enjoys composing music, scuba-diving, traveling and hiking.
Host: Professor Richard Leahy
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
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. -
Fall 2018 Joint CSC@USC/CommNetS-MHI Seminar Series
Mon, Jan 28, 2019 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Frank Lewis, http://csc.usc.edu/seminars/2019Spring/lewis.html
Talk Title: Reinforcement learning structures for real-time optimal control and differential games
Abstract: This talk will discuss some new adaptive control structures for learning online the solutions to optimal control problems and multi-player differential games. Techniques from reinforcement learning are used to design a new family of adaptive controllers based on actor-critic mechanisms that converge in real time to optimal control and game theoretic solutions. Continuous-time systems are considered. Application of reinforcement learning to continuous-time (CT) systems has been hampered because the system Hamiltonian contains the full system dynamics. Using our technique known as Integral Reinforcement Learning (IRL), we will develop reinforcement learning methods that do not require knowledge of the system drift dynamics. In the linear quadratic (LQ) case, the new RL adaptive control algorithms learn the solution to the Riccati equation by adaptation along the system motion trajectories. In the case of nonlinear systems with general performance measures, the algorithms learn the (approximate smooth local) solutions of HJ or HJI equations. New algorithms will be presented for solving online the non zero-sum and zero-sum multi-player games. Each player maintains two adaptive learning structures, a critic network and an actor network. The result is an adaptive control system that learns based on the interplay of agents in a game, to deliver true online gaming behavior. A new Experience Replay technique is given that uses past data for present learning and significantly speeds up convergence. New methods of Off-policy Learning allow learning of optimal solutions without knowing any dynamic information. New RL methods in Optimal Tracking allow solution of the Output Regulator Equations for heterogeneous multi-agent systems.
Biography: Member, National Academy of Inventors. Fellow IEEE, Fellow IFAC, Fellow AAAS, Fellow U.K. Institute of Measurement & Control, PE Texas, U.K. Chartered Engineer. UTA Distinguished Scholar Professor, UTA Distinguished Teaching Professor, and Moncrief-O'Donnell Chair at The University of Texas at Arlington Research Institute. Qian Ren Thousand Talents Consulting Professor, Northeastern University, Shenyang, China. Ranked at position 84 worldwide, 64 in the USA, and 3 in Texas of all scientists in Computer Science and Electronics, by Guide2Research. Bachelor's Degree in Physics/EE and MSEE at Rice University, MS in Aeronautical Engineering at the University of Western Florida, Ph.D. at Georgia Tech. He works in feedback control, reinforcement learning, intelligent systems, and distributed control systems. Author of 7 U.S. patents, 410 journal papers, 426 conference papers, 20 books, 48 chapters, and 12 journal special issues. He received the Fulbright Research Award, NSF Research Initiation Grant, ASEE Terman Award, Int. Neural Network Soc. Gabor Award 2009, U.K. Inst. Measurement & Control Honeywell Field Engineering Medal 2009. Received AACC Ragazzini Education Award 2018, IEEE Computational Intelligence Society Neural Networks Pioneer Award 2012 and AIAA Intelligent Systems Award 2016. IEEE Control Systems Society Distinguished Lecturer. Project 111 Professor at Northeastern University, China. Distinguished Foreign Scholar at Chongqing Univ. China. Received Outstanding Service Award from Dallas IEEE Section, selected as Engineer of the Year by Ft. Worth IEEE Section. Listed in Ft. Worth Business Press Top 200 Leaders in Manufacturing. Received the 2010 IEEE Region 5 Outstanding Engineering Educator Award and the 2010 UTA Graduate Dean's Excellence in Doctoral Mentoring Award. Elected to UTA Academy of Distinguished Teachers 2012. Texas Regents Outstanding Teaching Award 2013. He served on the NAE Committee on Space Station in 1995.
Host: Petros A Ioannou, ioannou@usc.edu
More Info: http://csc.usc.edu/seminars/2019Spring/lewis.html
More Information: 19.01.28 Frank Lewis CSCUSC Seminar.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Brienne Moore
Event Link: http://csc.usc.edu/seminars/2019Spring/lewis.html
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Center for Cyber-Physical Systems and Internet of Things and Ming Hsieh Institute Seminar Series
Wed, Jan 30, 2019 @ 03:00 PM - 04:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Babak Hassibi, Electrical Engineering at the California Institute of Technology
Talk Title: Control and Communication of Cyber-Physical Systems over Low-Power Lossy Links
Series: Center for Cyber-Physical Systems and Internet of Things
Abstract: Many emerging cyber-physical systems, for example those arising in the internet-of-things, will operate at very low power over lossy communication links. This creates a very tight set of constraints on the transmit power, bit rate, and tolerable delay, which, if not appropriately dealt with, can lead to severe loss of performance. We will describe three novel approaches for addressing the control and communication challenges in such cyber-phyical systems. We study the problem of minimizing an LQG control cost over a rate-constrained channel, the design of tree codes for real-time control over lossy links, and the development of a new modulation scheme for low power blind communications called MOCZ (modulation over conjugate zeros).
Biography: Babak Hassibi is the inaugural Mose and Lillian S. Bohn Professor of Electrical Engineering at the California Institute of Technology, where he has been since 2001, From 2011 to 2016 he was the Gordon M Binder/Amgen Professor of Electrical Engineering and during 2008-2015 he was Executive Officer of Electrical Engineering, as well as Associate Director of Information Science and Technology. Prior to Caltech, he was a Member of the Technical Staff in the Mathematical Sciences Research Center at Bell Laboratories, Murray Hill, NJ. He obtained his PhD degree from Stanford University in 1996 and his BS degree from the University of Tehran in 1989. His research interests span various aspects of information theory, communications, signal processing, control, and machine learning. He is an ISI highly cited author in Computer Science and, among other awards, is the recipient of the US Presidential Early Career Award for Scientists and Engineers (PECASE) and the David and Lucille Packard Fellowship in Science and Engineering. He is General co-Chair of the 2020 IEEE International Symposium on Information Theory (ISIT 2020).
Host: Paul Bogdan
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.
