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Events for the 5th week of November
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Fall 2018 Joint CSC@USC/CommNetS-MHI Seminar Series
Mon, Nov 26, 2018 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Geir Dullerud, University of Illinois Urbana-Champaign
Talk Title: Automata-switched systems, decentralized control, and team games
Abstract: This seminar is inspired from a practical perspective by recent advances in computing, sensing and networking hardware that make reconfigurable multiagent systems both technologically and economically feasible on a widespread scale. Switching is a common feature in systems that are comprised of interacting software and physical processes, and in this talk we will focus on a special type of hybrid model called an automaton-switched linear system. These models are closely related to Markovian jump linear systems, and contain both discrete and continuous states, where discrete states evolve according to automata, or more general transition systems, and continuous states evolve according to linear dynamics influenced by the discrete states. We will discuss how such systems can be automatically analyzed using ideas from control theory and semidefinite programming, and will provide solutions to several synthesis problems in this framework, including for instance the long-studied moving horizon problem, and the decentralized control problem for systems with nested structure. We will also present results on a particular class of team games in which players have incomplete model knowledge individually, but jointly know the global system dynamics. The HoTDeC multi-vehicle testbed will also be presented, along with implementations of the above results on indoor UAVs.
Biography: Geir E. Dullerud is the W. Grafton and Lillian B. Wilkins Professor in Mechanical Engineering at the University of Illinois at Urbana-Champaign. There he is also a member of the Coordinated Science Laboratory, where he is Director of the Decision and Control Laboratory (21 faculty); he is an Affiliate Professor of both Computer Science, and Electrical and Computer Engineering. He has held visiting positions in Electrical Engineering KTH, Stockholm (2013), and Aeronautics and Astronautics, Stanford University (2005-2006). Earlier he was on faculty in Applied Mathematics at the University of Waterloo (1996-1998), after being a Research Fellow at the California Institute of Technology (1994- 1995), in the Control and Dynamical Systems Department. He holds a PhD in Engineering from Cambridge University. He has published two books: A Course in Robust Control Theory, Texts in Applied Mathematics, Springer, 2000, and Control of Uncertain Sampled-data Systems, Birkhauser 1996. His areas of current research interest include convex optimization in control, cyber-physical system security, cooperative robotics, stochastic simulation, and hybrid dynamical systems. In 1999 he received the CAREER Award from the National Science Foundation, and in 2005 the Xerox Faculty Research Award at UIUC. He is a Fellow of both IEEE (2008) and ASME (2011). He is the General Chair of the upcoming IFAC workshop Distributed Estimation and Control in Networked Systems (NECSYS) to be held in Chicago in 2019.
Host: Mihailo Jovanovic, mihailo@usc.edu
More Info: http://csc.usc.edu/seminars/2018Fall/dullerud.html
More Information: 18.11.26_Geir Dullerud 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/2018Fall/dullerud.html
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Decentralized Signal Processing and Distributed Control for Collaborative Autonomous Sensor Networks
Wed, Nov 28, 2018 @ 12:00 PM - 01:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Ryan Alan Goldhahn & Priyadip Ray, Lawrence Livermore National Laboratory
Talk Title: Decentralized Signal Processing and Distributed Control for Collaborative Autonomous Sensor Networks
Series: Center for Cyber-Physical Systems and Internet of Things
Abstract: Collaborative autonomous sensor networks have recently been used in many applications including inspection, law enforcement, search and rescue, and national security. They offer scalable, low-cost solutions which are robust to the loss of multiple sensors in hostile or dangerous environments. While often comprised of less capable sensors, the performance of a large network can approach the performance of far more capable and expensive platforms if nodes are effectively coordinating their sensing actions and data processing. This talk will summarize work to date at LLNL on distributed signal processing and decentralized optimization algorithms for collaborative autonomous sensor networks, focusing on ADMM-based solutions for detection/estimation problems and sequential and/or greedy optimization solutions which maximize submodular functions such as mutual information.
Biography: Ryan Goldhahn holds a Ph.D. in electrical engineering from Duke University with a focus in statistical and model-based signal processing. Ryan joined the NATO Centre for Maritime Research and Experimentation (CMRE) as a researcher in 2010 and later as the project lead for an effort to use multiple unmanned underwater vehicles (UUVs) to detect and track submarines using multi-static active sonar. In this work he developed collaborative autonomous behaviors to optimally reposition UUVs to improve tracking performance without human intervention. He led several experiments at sea with submarines from multiple NATO nations. At LLNL Ryan has continued to work and lead projects in collaborative autonomy and model-based and statistical signal processing in various applications. He has specifically focused on decentralized detection/estimation/tracking and optimization algorithms for autonomous sensor networks.
Priyadip Ray received a Ph.D. degree in electrical engineering from Syracuse University in 2009. His Ph.D. dissertation received the Syracuse University All-University Doctoral Prize. Prior to joining LLNL, Dr. Ray was an assistant professor at the Indian Institute of Technology (IIT), Kharagpur, India where he supervised a research group of approximately 10 scholars in the areas of statistical signal processing, wireless communications, optimization, machine learning and Bayesian non-parametrics. Prior to this he was a research scientist with the Department of Electrical and Computer Engineering at Duke University. Dr. Ray has published close to 40 research articles in various highly-rated journals and conference proceedings and is also a reviewer for leading journals in the areas of statistical signal processing, wireless communications and data science. At LLNL, Dr. Ray has been the PI/Co-I on multiple LDRDs as well as a DARPA funded research effort in the areas of machine learning for healthcare and collaborative autonomy.
Host: Paul Bogdan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Talyia White
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Ming Hsieh Institite: Emerging Trends Seminar Series
Thu, Nov 29, 2018 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: C.-C. Jay Kuo, Distinguished Professor of Electrical Engineering-Systems and Computer Science, Ming Hsieh Department of Electrical Engineering
Talk Title: Interpretable Convolutional Neural Networks (CNNs) via Feedforward Design
Series: Emerging Trends
Abstract: Given a convolutional neural network (CNN) architecture, its network parameters are determined by backpropagation (BP). In contrast with the BP design, we propose a feedforward (FF) and interpretable design with the LeNet-5 as an illustrative example. The FF design is a data-centric approach that derives network parameters based on training data statistics layer by layer in one pass. To build the convolutional layers, we develop a new signal transform, called the Saab (Subspace approximation with adjusted bias) transform. The bias in filter weights is chosen to annihilate nonlinearity of the activation function. To build the fully-connected (FC) layers, we adopt a label-guided linear least squared regression (LSR) method. The FF design is more computationally efficient and robust against adversarial attacks than the traditional BP design. The classification performances of BP-designed and FF-designed CNNs on the MNIST and the CIFAR-10 datasets are compared. Finally, we comment on the relationship between BP and FF designs by examining their cross-entropy values at nodes of intermediate layers.
Biography: Dr. C.-C. Jay Kuo received his Ph.D. degree from the Massachusetts Institute of Technology in 1987. He is now with the University of Southern California (USC) as Director of the Media Communications Laboratory and Distinguished Professor of Electrical Engineering and Computer Science. His research interests are in the areas of media processing, compression and understanding. Dr. Kuo was the Editor-in-Chief for the IEEE Trans. on Information Forensics and Security in 2012-2014. Dr. Kuo received the 1992 National Science Foundation Young Investigator (NYI) Award, the 1993 National Science Foundation Presidential Faculty Fellow (PFF) Award, the 2010 Electronic Imaging Scientist of the Year Award, the 2010-11 Fulbright-Nokia Distinguished Chair in Information and Communications Technologies, the 2011 Pan Wen-Yuan Outstanding Research Award, the 2014 USC Northrop Grumman Excellence in Teaching Award, the 2016 USC Associates Award for Excellence in Teaching, the 2016 IEEE Computer Society Taylor L. Booth Education Award, the 2016 IEEE Circuits and Systems Society John Choma Education Award, the 2016 IS&T Raymond C. Bowman Award, and the 2017 IEEE Leon K. Kirchmayer Graduate Teaching Award. Dr. Kuo is a Fellow of AAAS, IEEE and SPIE. He has guided 147 students to their Ph.D. degrees and supervised 27 postdoctoral research fellows. Dr. Kuo is a co-author of 275 journal papers, 900 conference papers and 14 books.
Host: MHI
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Benjamin Paul
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MHI Research & Technology Seminar
Thu, Nov 29, 2018 @ 01:00 PM - 02:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Ruirui Huang, Senior Staff Architect/Director of Cloud Architecture at Alibaba Cloud
Talk Title: Security Architectural Design and Challenges in the Cloud
Series: MHI Research & Technology Seminar
Abstract: I will introduce the multi-layered security architectural design of Alibaba Cloud. Specifically, several technologies and mechanisms in each layer will be highlighted and discussed in terms of their importance and the security purposes which they serve. Additionally, I will raise several security challenges in today's cloud computing domain, and discuss how one might address them today and if there is a better solution in the future.
Biography: Dr. Ruirui Huang is a Senior Staff Architect/Director of Cloud Architecture at Alibaba Cloud (US office, based in Seattle, WA). He is responsible for overseeing and developing the Alibaba Cloud Platform Architecture, with a focus on the secure cloud computing architecture. He is also the author of Alibaba Cloud Security White-paper which was published earlier in 2018. Prior joining Alibaba Cloud, he was a Senior Security Architect at Intel, responsible for multiple Server/PC/Mobile SoCs security architectural designs.
Dr. Ruirui Huang graduated with a Ph.D. degree from the ECE department of the Cornell University in 2013, with research works and interests in the field of computer architectural support of security, reliability, and availability in today's computing world.
Host: MHI
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Benjamin Paul