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PhD Defense: Compression of Signal on Graphs with Application to Image and Video Coding
Tue, Sep 05, 2017 @ 04:00 PM - 06:00 PM
Ming Hsieh Department of Electrical Engineering
Workshops & Infosessions
Graph is a generic data structure that is useful in representing signals in various applications. In this thesis, we discuss several transform designs based on graph representation and the application in multimedia compression. Graphs can adapt to local characteristics, e.g. edges, and therefore provide more flexibilities than conventional transforms, e.g. Discrete Cosine Transform(DCT). A frequency interpretation for signal on graphs can be derived using Graph Fourier Transform (GFT). By properly adjusting the graph structure based on signal characteristics, GFT can provide compact representation even for signals with discontinuities. However, the transform requires high complexity in implementation, making it less applicable in signals of large size, e.g. video sequences. In our work, we develop a transform coding scheme based on a low complexity lifting transform on graphs. More specifically, we focus on two problems in the design of lifting transform, namely the design of bipartition and bipartite graph approximation. For the application, we consider two types of multimedia signals, including regular signals on 2D grid and signals that are irregularly distributed. For the former one, we consider the compression of intra-predicted video residuals. The data contain significant edge structures, which are difficult to be represented efficiently with existing transform coding standards. We also discuss different types of edge models for intra and inter-predicted video residuals in terms of the coding efficiency in GFT. For the other type of signal, we discuss the coding scheme for un-demosaicked light field images. Without demosaicking from the raw data captured using Color Filter Array (CFA) to full-color sub-aperture images, we can avoid large redundancies introduced from color interpolation. However, the pixels of each color channel will be distributed irregularly within each sub-aperture image, and therefore motivates the application of graph representation. A novel intra-prediction scheme and graph construction based on sparsely distributed pixels are proposed. Theoretical interpretation and comprehensive experimental results are presented for proposed methods.
More Information: Yung-Hsuan Chao Seminar.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Posted By: Gloria Halfacre
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Sophomore Info Session
Wed, Sep 06, 2017 @ 04:00 PM - 05:00 PM
Ming Hsieh Department of Electrical Engineering
Workshops & Infosessions
Dear BSEE Sophomores,
You're invited to Meet Your EE Dept. on Wed., Sept. 6 at 4:00 pm in EEB 248.
Delve into the BSEE requirements, undergraduate research opportunities and graduate degrees - PDP and PhD (not too early!). Profs. Maby and Redekopp will be there to answer any questions you have about anything. Meet your advisors.
See you then!
EE Student ServicesLocation: Hughes Aircraft Electrical Engineering Center (EEB) - 102
Audiences: Undergrad
Posted By: Benjamin Paul
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Towards Accelerator-Rich Architectures and Systems
Thu, Sep 07, 2017 @ 02:00 PM - 03:15 PM
Ming Hsieh Department of Electrical Engineering
Conferences, Lectures, & Seminars
Speaker: Zhenman Fang, UCLA
Talk Title: Towards Accelerator-Rich Architectures and Systems
Abstract: With Intel's $16.7B acquisition of Altera and the deployment of FPGAs in major cloud service providers including Microsoft and Amazon, we are entering a new era of customized computing. In future architectures and systems, it is anticipated that there will be a sea of heterogeneous accelerators customized for important application domains, such as machine learning and personalized healthcare, to provide better performance and energy-efficiency. Many research problems are still open, such as how to efficiently integrate accelerators into future chips and commodity datacenters, and how to program such accelerator-rich architectures and systems.
In this talk, I will first briefly explain how customized accelerators can achieve orders-of-magnitude performance improvement, based on our open-source simulator PARADE [ICCAD 2015, tutorials at ISCA 2015 & MICRO 2016]. Second, I will present our initial work on CPU-accelerator co-design, where we provide efficient and unified address translation support between CPU cores and accelerators [HPCA 2017 Best Paper Nominee]. It shows that a simple two-level TLB design for accelerators plus the host core MMU for accelerator page walking can be very efficient. On average, it achieves 7.6x speedup over the naïve IOMMU and there is only 6.4% performance gap to the ideal address translation. Finally, I will present the open-source Blaze system that provides programming and runtime support to enable easy and efficient FPGA accelerator deployment in datacenters [HotCloud 2016, ACM SOCC 2016]. Blaze abstracts accelerators-as-a-service, and bridges the gap between big data applications (e.g., Apache Spark programs) and emerging accelerators (e.g., FPGAs). By plugging a PCIe-based FPGA board into each CPU server, it can improve the system throughput by several folds for a range of applications.
Biography: Dr. Zhenman Fang is a postdoc in the Computer Science Department, UCLA, working with Prof. Jason Cong and Prof. Glenn Reinman. He is a member of the NSF/Intel funded multi-university Center for Domain-Specific Computing (CDSC) and the SRC/DARPA funded multi-university Center for Future Architectures Research (C-FAR). Zhenman received his PhD in June 2014 from Fudan University, China and spent the last 15 months of his PhD program visiting University of Minnesota at Twin Cities. Zhenman's research lies at the boundary of heterogeneous and energy-efficient computer architectures, big data workloads and systems, and system-level design automation. He has published 10+ papers in top venues that span across computer architecture (HPCA, TACO, ICS), design automation (DAC, ICCAD, FCCM, IEEE Design & Test), and cloud computing (ACM SOCC). He received several awards, including a postdoc fellowship from UCLA Institute of Digital Research and Education, a best paper nominee of HPCA 2017, a best demo award at the C-FAR center annual review. More details can be found in his personal website: https://sites.google.com/site/fangzhenman/.
Host: Xuehai Qian, x04459, xuehai.qian@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Posted By: Gerrielyn Ramos
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2nd Annual Undergraduate Open House
Fri, Sep 08, 2017 @ 03:00 PM - 05:00 PM
Ming Hsieh Department of Electrical Engineering
Student Activity
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Posted By: Cathy Huang
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Center for Systems and Control (CSC@USC) and Ming Hsieh Institute for Electrical Engineering
Mon, Sep 11, 2017 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical Engineering
Conferences, Lectures, & Seminars
Speaker: Ramtin Pedarsani, University of California, Santa Barbara
Talk Title: Robust Scheduling for Flexible Stochastic Networks
Abstract: Modern large-scale stochastic systems face much demand and processing variability, and a key challenge is the design of efficient control and scheduling policies that are robust to these uncertainties. In this talk, I will present several robust scheduling policies for stochastic models with applications to emerging sectors such as data centers and intelligent transportation systems. In the first part, I present a robust scheduling policy with performance guarantee, for a novel stochastic model of job scheduling in data centers, where jobs are represented as directed acyclic graphs (DAG). I will then visit the long-standing open problem on the stability of of the longest-queue-first scheduling policy for multiclass open queueing networks, and resolve this problem for an important special case. In the second part of the talk, I focus on transportation networks. I develop the first exact analysis of fixed-time control for urban networks, and briefly mention a few opportunities and challenges in exploiting autonomous vehicles for enhancing network's performance.
Biography: Ramtin Pedarsani is an assistant professor in the ECE department at UCSB. He obtained his Ph.D. in Electrical Engineering and Computer Sciences from UC Berkeley in 2015. He received his M.Sc. degree at EPFL in 2011 and his B.Sc. degree at the University of Tehran in 2009. His research interests include stochastic networks, information and coding theory, and transportation systems. He is the recipient of the best paper award in the IEEE International Conference on Communications (ICC) in 2014.
Host: Insoon Yang, x.02351, insoonya@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Posted By: Gerrielyn Ramos
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Center for Cyber-Physical Systems and Internet of Things and Ming Hsieh Institute for Electrical Engineering Joint Seminar Series on Cyber-Physical Systems
Wed, Sep 13, 2017 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical Engineering
Conferences, Lectures, & Seminars
Speaker: Nikos Arechiga, Toyota Research Institute
Talk Title: Scalable Automatic Reasoning in Model-Based Development
Abstract: Recent progress in vehicle autonomy and robotics has increased the importance of system assurance, ranging from safety to security concerns. These assurances require systems that are able to reason about large and complex system designs, often containing large lookup tables as well as AI components.
This talk presents a general-purpose technique that leverages machine learning to automatically learn logical antecedents and consequents to simplify a complex formal verification task.
We also describe a specialization of this technique that has been used within Toyota to reason about software with large lookup tables, including a public benchmark.
Finally, we look to the future and describe emerging research directions in automatic reasoning.
Biography: Dr. Nikos Arechiga graduated with a Ph. D. in Electrical and Computer Engineering at Carnegie Mellon working with Professor Bruce Krogh. His graduate work touched on automatic inference of barrier certificates to simplify proofs of safety as well as techniques for provably-correct controller synthesis.
He has been working at Toyota for two years, and has been involved with developing scalable reasoning techniques to address complex models with lookup tables, and is recently considering the problem of reasoning about AI components.
Host: Paul Bogdan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Posted By: Estela Lopez
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High-Level Program Optimizations for Data Analytics
Thu, Sep 14, 2017 @ 02:00 PM - 03:15 PM
Ming Hsieh Department of Electrical Engineering
Conferences, Lectures, & Seminars
Speaker: Yufei Ding, University of California at Santa Barbara
Talk Title: High-Level Program Optimizations for Data Analytics
Abstract: Many modern applications, especially those data analytics, often spend a large number of cycles on unnecessary computations. To find a document most similar to a query document, for instance, these applications typically would need to examine hundreds of thousands of other documents (that are not the most similar ones) in the dataset. Such redundant computations have been hidden in the useful instructions of the applications and are elusive for traditional compiler-based code optimizations. My work harnesses these hidden but significant optimization opportunities by raising the level of program optimizations from implementations to algorithms, and from instructions to formulas.
Biography:
Yufei Ding will soon join the department of Computer Science, University of California at Santa Barbara as an assistant professor. She received her Ph.D. in the Computer Science from North Carolina State University, and B.S. and M.S. in Physics from University of Science and Technology of China and The College of William and Mary respectively. In 2012, she started her Ph.D. study in Computer Science. Her research interest resides at the intersection of Compiler Technology and (Big) Data Analytics, with a focus on enabling HighI-Level Program Optimizations for data analytics and other data-intensive applications. Yufei has been actively publishing in major venues in both computer systems and data analytics areas, such as ASPLOS, PLDI, OOPSLA, VLDB, ICDE, and ICML. She was the receipt of NCSU Computer Science Outstanding Research Award in 2016.
Host: Xuehai Qian, x04459, xuehai.qian@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Posted By: Gerrielyn Ramos
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Internet of Skills-Enabled by 5G Decoupled Uplink & Downlink
Fri, Sep 15, 2017 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical Engineering
Conferences, Lectures, & Seminars
Speaker: Mischa Dohler, King's College London, UK
Talk Title: Internet of Skills-Enabled by 5G Decoupled Uplink & Downlink
Abstract: With the emergence of an ultra-responsive and reliable 5G 'Tactile Internet,' advanced techniques in robotics and artificial intelligence, we advocate for the emergence of an 'Internet of Skills' which allows the "transmission of labor" globally. It will invoke an important shift from content-delivery to skillset-delivery networks, where engineers would service cars or surgeons performing critical operations anywhere on the planet. For this to work, however, we require some fundamental changes to wireless communications systems. This presentation will look at the disruptive technology approaches in wireless 5G, notably the impact of decoupling up and downlinks; as well as the impact it has on different industry verticals.
Biography: Mischa Dohler is full Professor in Wireless Communications at King's College London, driving cross-disciplinary research and innovation in technology, sciences and arts. He is the Director of the Centre for Telecommunications Research, co-founder of the pioneering smart city company Worldsensing, Fellow of the IEEE, the Royal Academy of Engineering and the Royal Society of Arts (RSA), and a Distinguished Member of Harvard Square Leaders Excellence.
He is a frequent keynote, panel and tutorial speaker, and has received numerous awards. He has pioneered several research fields, contributed to numerous wireless broadband, IoT/M2M and cyber security standards, holds a dozen patents, organized and chaired numerous conferences, was the Editor-in-Chief of two journals, has more than 200 highly-cited publications, and authored several books.
He acts as policy, technology and entrepreneurship adviser, examples being Richard Branson's Carbon War Room, former Minister David Willetts' 8 Great Technology Fund, UK Regulator Ofcom, UK Ministries, No 10, EPSRC ICT Strategy Advisory Team, European Commission, Tech London Advocate, ISO Smart City working group, and various start-ups.
He is also an entrepreneur; composer & pianist with 5 albums on iTunes and an artist-verified Spotify account; as well as fluent in 6 languages. He has talked twice at TEDx. He had coverage by national and international TV & radio, and his contributions have featured on the BBC, the Wall Street Journal and many others.
Host: Urbashi Mitra, ubli@usc.edu, EEB 536, x04667
Location: 248
Audiences: Everyone Is Invited
Posted By: Gerrielyn Ramos
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Ming Hsieh Institute Seminar Series on Integrated Systems
Fri, Sep 15, 2017 @ 01:30 PM - 03:30 PM
Ming Hsieh Department of Electrical Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Vesna Radisic, Principle Scientist, Northrop Grumman
Talk Title: Engineered and Full 3D RF Materials
Host: Profs. Hossein Hashemi, Mike Chen, Mahta Moghaddam, and Dina El-Damak
More Information: MHI Seminar Series IS -Vesna Radisic.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Posted By: Jenny Lin
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Center for Systems and Control (CSC@USC) and Ming Hsieh Institute for Electrical Engineering
Mon, Sep 18, 2017 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical Engineering
Conferences, Lectures, & Seminars
Speaker: Andrzej Banaszuk, Andrew Sparks, and Fu Lin, United Technologies Research Center
Talk Title: Systems and Control Research at United Technologies Research Center
Abstract: This presentation will give a broad overview of research at UTRC's Systems Department, with particular focus on the areas of autonomous and intelligent systems, robotics, and control of complex systems. The research is conducted by a diverse team of researchers in dynamical systems, advanced control, applied mathematics, and human factors. Autonomous and intelligent systems research for aerial and ground robotics includes intelligent system architecture, human-machine systems, perception, collaborative motion planning with dynamic collision avoidance, manipulation, and formal verification. Research for large-scale, complex, and interconnected systems includes systematic methods to functionally decompose complex, interconnected systems to inform control architecture as well as approaches to sparse and distributed control. The presentation will conclude with a discussion of existing and future career and internship opportunities in the broad area of autonomous and intelligent systems, controls, and robotics.
Biography: http://csc.usc.edu/seminars/2017Fall/banaszuk_sparks_lin.html
Host: Mihailo Jovanovic, mihailo@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Posted By: Gerrielyn Ramos
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Center for Cyber-Physical Systems and Internet of Things and Ming Hsieh Institute for Electrical Engineering Joint Seminar Series on Cyber-Physical Systems
Wed, Sep 20, 2017 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical Engineering
Conferences, Lectures, & Seminars
Speaker: BaekGyu Kim, Toyota InfoTechnology Center
Talk Title: Test Specification and Generation for Connected and Autonomous Vehicle in Virtual Road Environment
Abstract: The trend of connected / autonomous features adds significant complexity to the traditional automotive systems. In order to improve driving safety and comfort, vehicles are expected to drive autonomously and/or to communicate with each other and infrastructures. Such complexity makes engineers harder to test correctness, performance or effectiveness of those driving features in the physical environment. In this talk, we introduce a virtual test framework that utilizes existing visualization engines (e.g., Unity3D, Unreal Engine or Prescan). In this test framework, a system component is integrated with a virtual vehicle that can be tested under a wide range of virtual road environments to overcome the limitation of the physical testing. In order to build such test environments, we introduce a formal way to specify geometric and behavioral aspects of the road environments using SMT constraints (Satisfiability Modulo Theories) and timed automata. We also introduce a systematic way to generate those road environments from the formal specification based on several test criteria. Finally, we show the applicability of the proposed road environment generation method using adaptive cruise control (an example of autonomous features) and right-turn pedestrian warning system (an example of connected features).
Biography: BaekGyu Kim earned B.S. and M.S. from Kyungpook National University in South Korea in 2007 and 2009, and earned Ph.D. in computer science from University of Pennsylvania in 2015. His research interest is applying various formal techniques to build safety-critical real-time embedded systems according to the model-based development paradigm. His doctoral dissertation topic was to design model-based implementation framework to assure the safety of infusion pump systems (medical device) as a part of Generic Infusion Pump project. After joining Toyota InfoTechnology Center, he started applying those techniques to analyze correctness and effectiveness of automotive systems.
Host: Paul Bogdan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Posted By: Estela Lopez
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Dramatic Improvements in Pre-silicon and Post-silicon Validation of Digital Systems with Quick Error Detection and Formal Methods
Thu, Sep 21, 2017 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical Engineering
Conferences, Lectures, & Seminars
Speaker: Clark Barrett, Stanford University
Talk Title: Dramatic Improvements in Pre-silicon and Post-silicon Validation of Digital Systems with Quick Error Detection and Formal Methods
Abstract: Ensuring the correctness of integrated circuits (ICs) is essential for ensuring the correctness, safety and security of the many electronic systems we rely on. However, the effort required to validate ICs continues to be a major bottleneck in modern system design. To make matters worse, difficult bugs still escape into post-silicon and even production systems. I will present a set of results based on Quick Error Detection (QED). The standard QED technique is a testing technique which drastically reduces error detection latency, the time elapsed between the occurrence of an error caused by a bug and its manifestation as an observable failure. I will then present two new techniques, Symbolic QED and Electrical QED which use formal methods to dramatically extend the reach of QED: to automatically detect and localize both logic and electrical bugs during both pre- and post-silicon validation. Experimental results collected from several commercial designs as well as hardware platforms demonstrate the effectiveness and practicality of these methods. For example, for a 500 million transistor multi-core IC, Symbolic QED automatically detected and localized difficult logic design bugs (the kind that could escape traditional simulation-based pre-silicon verification) in only a few hours (~ 8 hours on average). This research was performed at Stanford University in collaboration with Prof. Subhasish Mitra, several graduate students, and several industrial collaborators.
Biography: Clark Barrett is an associate professor (research) of computer science at Stanford University, with expertise in constraint solving and its applications to verification. His PhD dissertation introduced a novel approach to constraint solving now known as satisfiability modulo theories (SMT). His subsequent work on SMT has been recognized with a best paper award at DAC, an IBM Software Quality Innovation award, the Haifa Verification Conference award, and first-place honors at the SMT, CASC, and SyGuS competitions. He was also an early pioneer in the development of formal hardware verification: at Intel, he collaborated on a novel theorem prover used to verify key microprocessor properties; and at 0-in Design Automation (now part of Mentor Graphics), he helped build one of the first industrially successful assertion-based verification tool-sets for hardware.
Host: Pierluigi Nuzzo, x09079, nuzzo@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Posted By: Gerrielyn Ramos
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Center for Cyber-Physical Systems and Internet of Things and Ming Hsieh Institute for Electrical Engineering Joint Seminar Series on Cyber-Physical Systems
Thu, Sep 21, 2017 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical Engineering
Conferences, Lectures, & Seminars
Speaker: Hong-Linh Truong, Priv.Doz and an Assistant Professor, TU Wien (Vienna University of Technology), Austria
Talk Title: Managing and Testing Ensembles of IoT, Network functions, and Clouds
Abstract: By leveraging virtualization and pay-per-use models, we believe that eventually applications will easily acquire IoT, network functions, and cloud services together to establish a virtual, unified resource ensemble across various subsystems from different IoT, network and cloud providers. But this will require us to research and develop various programming and management utilities. In this talk, we will first discuss the necessity and feasibility of application-level resource slice provisioning. We will overview our SINC - Slicing IoT, Network functions, and Clouds - as an approach for provisioning resource slices of end-to-end IoT, network functions, and cloud capabilities for novel requirements from a wide range of IoT/CPS applications. We will present several works on service engineering analytics for SINC, including harmonizing IoT, network functions, and cloud resources, supporting end-to-end monitoring and analytics, and testing uncertainties.
Some links to related tools:
http://rdsea.github.io/
http://sincconcept.github.io/
http://sincconcept.github.io/HINC/
https://github.com/tuwiendsg/COMOT4U/
http://tuwiendsg.github.io/iCOMOT/
Biography: Hong-Linh Truong is currently a Priv.Doz and an assistant professor for Service Engineering Analytics at TU Wien (Vienna University of Technology), Austria. He received an engineer degree from the Bach Khoa University (HoChiMinh City University of Technology), Vietnam, in 1998, a PhD degree, in 2005, and a Habilitation, in 2013, both from TU Wien, Austria; all in computer science and engineering. His main research interest focuses Systems, Software, Data and Service Engineering Analytics by developing novel techniques and tools for monitoring, analyzing, and optimizing functions, performance, data quality, elasticity, and uncertainties associated with systems, software, data and services. His research has been applied to: Monitoring, Analysis and Optimization Techniques for Programs, Data and Systems; Parallel, Grid and Cloud Computing, and IoT; Data Service Models and Analytics; Socio-technical Services Engineering; and Elastic Computing. Furthermore, he is interested in (free) ICT solutions for (under) developing countries. He had delivered several invited talks and he published more than 180 refereed papers in books, conferences/workshops and journals. He (co)receives an outstanding paper award, seven best paper awards, one best paper run-up award, and one best poster award. Contact him at truong@dsg.tuwien.ac.at http://dsg.tuwien.ac.at/staff/truong .
Host: Bhaskar Krishnamachari and Paul Bogdan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Posted By: Estela Lopez
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A Model-Based Iterative Reconstruction Approach to Tunable Diode Laser Absorption Tomograph
Fri, Sep 22, 2017 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical Engineering
Conferences, Lectures, & Seminars
Speaker: Zeeshan Nadir, Electrical and Computer Engineering, Purdue University
Talk Title: A Model-Based Iterative Reconstruction Approach to Tunable Diode Laser Absorption Tomography
Abstract: Many imaging and sensing problems in the fields of medical imaging, computer vision, machine learning, communications and signal processing etc. can be posed as inverse problems. Broadly, an inverse problem consists of recovering some underlying signal of interest that leads to a directly observable measurement dataset where the measurement dataset may be corrupted by noise. In the presence of sufficient quantity of good quality measurement dataset, the inversion problem can often be solved by direct methods often involving closed form inverse formulas like filtered back projection. However, when the measurement data contains noise or is extremely sparse, then such conventional techniques do not work. Tunable Diode Laser Absorption Tomography (TDLAT) is such an ill-posed nonlinear inverse problem where 2D concentration and temperature images are required to be reconstructed from a handful of projection measurements.
Bayesian methods are a probabilistic approach to reconstruct signals by incorporating prior information about the signals in the form of a prior probability distribution. Typical 2D prior models like Markov Random Field enforce local smoothness on the images by penalizing differences between neighboring pixels. However, the major limitation of such prior models is that they cannot express non-homogeneous and non-Gaussian characteristics of the images and therefore cannot model the long-range correlations between image pixels. In this presentation, I shall present a Gaussian Mixture Model as a prior distribution which can be trained with a few training examples. In order to show the utility of this approach, I shall apply it to Tunable Diode Laser Absorption Tomography problem. I shall formulate the reconstruction problem as a Maximum-aposteriori estimation problem. I shall present an efficient multigrid algorithm to perform the resulting optimization. The results using simulated datasets show that the proposed approach can reduce reconstruction error while also resulting in a computationally efficient algorithm.
Biography: Zeeshan Nadir is a Ph.D. candidate in the school of Electrical and Computer Engineering, Purdue University, West Lafayette, IN. In Summer 2016, he was an intern at MathWorks, Inc., Natick, MA, where he worked on MATLAB coder package. He developed a new functionality in MATLAB Coder which has been incorporated in MATLAB R2017a release. His research interests include statistical signal processing, inverse problems, computational imaging, machine learning and computer vision.
Host: Hosted by Prof. Richard Leahy
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Posted By: Talyia White
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MHI Pioneer Series
Mon, Sep 25, 2017 @ 03:00 AM - 05:00 PM
Ming Hsieh Department of Electrical Engineering
Conferences, Lectures, & Seminars
Speaker: Andrew Viterbi, University of Southern California Trustee, Presidential Chair, and Professor of Electrical Engineering
Talk Title: "It was the worst of times, it was the best of times." (with apologies to Mr. Dickens)
Series: MHI Pioneer Series
Abstract: The last two thirds of the 20th Century was a period of tremendous upheaval and progress, social, political and especially technological. This was the period during which I pursued two careers which were tightly intertwined. Curiously both were also influenced by our nation's most threatening competitor, Russia.
The first was my academic career and the second my entrepreneurial career, both of which covered over thirty years, with considerable overlap. Though unrecognized at the time, my academic research had roots in the work of the Russian mathematician Andrei Markov, while with full recognition, my entrepreneurial career was launched and initially supported by our Defense research efforts to counter the Soviet threat.
From 1957, when I arrived at Caltech's JPL just before the launch of Sputnik, until 2000 when I retired from Qualcomm, I was involved in furthering the knowledge, understanding and implementation of wireless digital communication, first for space and ultimately for cellular networks. My academic achievements, which have given me the most satisfaction, were primarily in the fields of synchronization and of error-suppressing coding. My entrepreneurial efforts were in support of the founding of two digital communication companies, Linkabit and Qualcomm, whose technologists achieved important breakthroughs through the practical realization of communication theory principles. Among these were the first Viterbi decoder now ubiquitous in digital wireless handsets, the first fully digitally implemented satellite modem, the first mobile satellite terrestrial network and the first spread spectrum digital cellular networks, which enabled the rise of a myriad of applications.
In the new millennium, to prevent boredom and counter aging, my time has been devoted partly to activities on corporate boards of startup companies in digital communication, data storage and their numerous applications. My Memoir, "Reflections of an Educator, Researcher and Entrepreneur," was published recently.
Host: Ming Hsieh Institute
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Posted By: Cathy Huang
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Center for Systems and Control (CSC@USC) and Ming Hsieh Institute for Electrical Engineering
Mon, Sep 25, 2017 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical Engineering
Conferences, Lectures, & Seminars
Speaker: Angelia Nedich, Arizona State University
Talk Title: Fast Distributed Algorithms for Optimization and Resource Sharing in Networks
Abstract: We will discuss the problems of distributed optimization over graphs. For the case of undirected graphs, we introduce a distributed algorithm, referred to as DIGing, which is a combination of a distributed inexact gradient method and a gradient-tracking mechanism. The DIGing algorithm uses doubly stochastic mixing matrices and employs fixed step-sizes and, yet, drives all agents' iterates to a common global minimizer. When the graphs are directed, in which case the implementation of doubly stochastic mixing matrices is unrealistic, we construct an algorithm that incorporates the push-sum protocol into the DIGing structure, thus obtaining Push-DIGing algorithm. Under the strong convexity assumption for the objective function, we prove that both algorithms converge at R-linear (geometric) rates, as long as the step-sizes do not exceed some upper bounds. We establish explicit convergence rate estimates for the convergence rates. When the graph is undirected, we show that the convergence rate of DIGing scales polynomially in the number of agents. We also provide some numerical experiments to demonstrate the efficacy of the proposed algorithms and to validate our theoretical findings. We then discuss the variants of these algorithms for resource allocation problems in graphs.
Biography: Angelia Nedich holds a Ph.D. from Moscow State University, Moscow, Russia, in Computational Mathematics and Mathematical Physics (1994), and a Ph.D. from Massachusetts Institute of Technology, Cambridge, USA in Electrical and Computer Science Engineering (2002). She has worked as a senior engineer in BAE Systems North America, Advanced Information Technology Division at Burlington, MA. She is the recipient of an NSF CAREER Award 2007 in Operations Research for her work in distributed multi-agent optimization. She is a recipient (jointly with her co-authors) of the Best Paper Award at the Winter Simulation Conference 2013 and the Best Paper Award at the International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt) 2015 (with co-authors). She has served as Associate Editor for IEEE Transactions on Automatic Control and Transactions of Control of Network Systems. She is currently serving on Editorial Board of SIAM Journal on Optimization and for INFORMS Operations Research. Her current interest is in large-scale optimization, games, control and information processing in networks.
Host: Mihailo Jovanovic, mihailo@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Posted By: Gerrielyn Ramos
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Center for Cyber-Physical Systems and Internet of Things and Ming Hsieh Institute for Electrical Engineering Joint Seminar Series on Cyber-Physical Systems
Wed, Sep 27, 2017 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical Engineering
Conferences, Lectures, & Seminars
Speaker: Eric Feron , Professor, Georgia Institute of Technology
Talk Title: 20 Years of Aerobatic Flight with Autonomous Air Vehicles
Abstract: The past 20 years have seen a remarkable evolution of the drone technology. Back in 1997, academia had to deal with heavy, bulky and expensive machines powered by cranky internal combustion engines. Unmanned vehicles today are a lot cheaper, lighter, and reliable, making them a lot more approachable by students and faculty alike. After tracing our research back to the late 1990s, this talk will introduce an aerobatic drone capable of producing reduced- or zero-gravity conditions at an affordable cost. The platform is still a prototype, but it captures most of the difficulties faced by the larger platform of our dreams. The controller design will be discussed, and a full non-linear maneuver stability analysis will be presented that mixes the concept of transverse dynamics with well-known concepts from robust control. This is joint work with John Hauser (U. Colorado, Boulder) and Pablo Afman (Georgia Tech).
Biography: Eric Feron is a professor at Georgia Tech, where he directs the Decision and Control Laboratory. His basic training is in applied mathematics, computer science, and operations research. His interests include aerospace systems and robotics. Noteworthy achievements include an airport congestion control algorithm now used at many major airports (1999), the first aerobatic autonomous air vehicle (2001), the english translation of Étienne Bézout's General Theory of Algebraic Equations (2006), and a course on cyber-physical systems offered by Georgia Tech as part of its Online Master of Science in Computer Science (2017).
Host: Paul Bogdan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Posted By: Estela Lopez
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Munushian Seminar - Ming C. Wu, Friday, September 22nd at 2:00pm in EEB 132
Fri, Sep 29, 2017 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical Engineering
Conferences, Lectures, & Seminars
Speaker: Ming C. Wu, University of California, Berkeley
Talk Title: Silicon Photonic MEMS
Abstract: Ming C. Wu is Nortel Distinguished Professor of Electrical Engineering and Computer Sciences at the University of California, Berkeley. He is also Co-Director of Berkeley Sensor and Actuator Center (BSAC) and Faculty Director of UC Berkeley Marvell Nanolab. Dr. Wu received his M.S. and Ph.D. in Electrical Engineering and Computer Sciences from the University of California, Berkeley in 1988. He has been with AT&T Bell Laboratories, Murray Hill (1988-1992) and UCLA (1993 to 2004) before joining the faculty at Berkeley. His research interests include optoelectronics, nanophotonics, MEMS, and optofluidics. He has published 8 book chapters, over 500 papers in journals and conferences, and 25 issued U.S. patents.
Prof. Wu is an IEEE Fellow, and a Packard Foundation Fellow (1992 - 1997). He received the 2007 Paul F. Forman Engineering Excellence Award, the 2017 C.E.K. Mees Medal from Optical Society of America, and the 2016 William Streifer Award from IEEE Photonics Society.
Biography: Ming C. Wu is Nortel Distinguished Professor of Electrical Engineering and Computer Sciences at the University of California, Berkeley. He is also Co-Director of Berkeley Sensor and Actuator Center (BSAC) and Faculty Director of UC Berkeley Marvell Nanolab. Dr. Wu received his M.S. and Ph.D. in Electrical Engineering and Computer Sciences from the University of California, Berkeley in 1988. He has been with AT&T Bell Laboratories, Murray Hill (1988-1992) and UCLA (1993 to 2004) before joining the faculty at Berkeley. His research interests include optoelectronics, nanophotonics, MEMS, and optofluidics. He has published 8 book chapters, over 500 papers in journals and conferences, and 25 issued U.S. patents.
Prof. Wu is an IEEE Fellow, and a Packard Foundation Fellow (1992 - 1997). He received the 2007 Paul F. Forman Engineering Excellence Award, the 2017 C.E.K. Mees Medal from Optical Society of America, and the 2016 William Streifer Award from IEEE Photonics Society.
Host: EE-Electrophysics
More Info: minghsiehee.usc.edu/about/lectures
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Posted By: Marilyn Poplawski
