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CESG Seminar: Abstraction and applied mathematics: functional analysis in the 20th century

CESG Seminar: Abstraction and applied mathematics: functional analysis in the 20th century

August 8 @ 4:00 pm - 5:00 pm

Join CESG and Prof. Seidman for some comments (primarily historical) on how we now think of Des and how Functional Analysis provides the essential framework for one to work with applications. Professor Thomas Seidman Department of Mathematics and Statistics University of Maryland, Baltimore County (UMBC) Host: P.R. Kumar


CESG: Distributed Algorithms for Cyberphysical Systems

CESG: Distributed Algorithms for Cyberphysical Systems

August 10 @ 2:30 pm - 4:00 pm

Abstract Cyberphysical Systems (CPS) are very large networks in which collaborating agents possessing sensing, communication and computation capabilities are interconnected for controlling physical entities. Applications are ubiquitous in sensor networks, robotics, transportation, and smart grids. In this talk, I will present distributed, asynchronous and real-time algorithms for CPS, and illustrate applications in transportation, robotics and cyber security of CPS. In specific: a) Distributed optimization: We propose a new block-coordinate operator splitting method that can handle a wide range of problems in multi-agent systems, signal processing and machine learning. We establish exponential convergence under a certain metric subregularity condition (which is weaker than strong convexity). We proceed to develop randomized distributed methods for multi-agent optimization, and exhibit our methods in the context of Network Utility Maximization and Distributed Model Predictive Control. On another front, we propose a novel exponentially converging gossip algorithm for GPS-free multi-agent localization. b) Travel time estimation: We propose and analyze a method for performing compressed sensing on an infinite data stream. Our protocol involves a) encoding, via compressively sampling sliding windows of the data stream, and b) decoding, by means of solving LASSO using a newly developed quasi-Newton proximal method with accelerated convergence rates. We apply our framework to the problem of sparse kernel density estimation, and delineate its advantages for adaptively learning travel time distributions in transportation networks in real-time. c) Cyber Security: We establish fundamental asymptotic bounds on the security of distributed protocols to collusion attacks. Our analysis enacts an encouraging result, in that the number of attackers that can be tolerated in large-scale CPS is ‘almost linear’ in the number of benign agents. Furthermore, we propose a theme for performing computations directly on encrypted data in a distributed fashion, and discuss its implications in the realm of secure cloud computing. Bio: Nick Freris is an assistant professor of Electrical and Computer Engineering at New York University Abu Dhabi (NYUAD), and a Global Network Assistant Professor at New York University Tandon School of Engineering. He is the director of Cyberphysical Systems Laboratory (CPSLab) at NYUAD, and a member of the Center for Cyber Security (CCS). He received the Diploma in Electrical and Computer Engineering from the National Technical University of Athens (NTUA), Greece in 2005, and the M.S. degree in Electrical and Computer Engineering, the M.S. degree in Mathematics, and the Ph.D. degree in Electrical and Computer Engineering all from the University of Illinois at Urbana-Champaign in 2007, 2008, and 2010, respectively. Dr. Freris’s research interests lie in the area of cyberphysical systems: distributed estimation, optimization and control, data mining/machine learning, cyber security, and applications in transportation, sensor networks and robotics. His research was recognized with the 2014 IBM High Value Patent award, two IBM invention achievement awards, and the Gerondelis foundation award. Previously, Dr. Freris was a senior researcher in the School of Computer and Communication Sciences at École Polytechnique Fédérale de Lausanne (EPFL), Switzerland, from 2012-2014, and a postdoctoral researcher in IBM Research – Zurich, Switzerland, from 2010-2012. Dr. Freris is a senior […]


CESG Fishbowl Seminar: Distributed Control of Large-Scale Infrastructure Networks

CESG Fishbowl Seminar: Distributed Control of Large-Scale Infrastructure Networks

August 11 @ 1:30 pm - 2:30 pm

Sivaranjani Seetharaman Graduate student, Dept. of Electrical Engineering University of Notre Dame Abstract: With the proposed development of smart cities around the world, research into novel scalable control techniques for large-scale infrastructure networks is becoming increasingly important. The first half of this talk will focus on disturbance management in networked systems by exploiting integrated communication infrastructure. It will be demonstrated that localization and attenuation of disturbances in distributed systems can be achieved by communicating information about the disturbance faster than its speed of propagation through the network. The role of communication delays and packet drops on disturbance localization will also be explored. In the second half of this talk, scalable dissipativity and passivity based control techniques for large-scale interconnected systems, specifically power grids, will be discussed. The modeling of a smart grid with distributed generation as a parameter varying system with passivity violations and the derivation of control designs that ensure stability and improve the performance of this system will be presented. This talk will also provide a brief overview of the research carried out in the Distributed Systems Lab at the University of Notre Dame. Bio: Sivaranjani Seetharaman is a graduate student in the Department of Electrical Engineering, University of Notre Dame. She obtained her undergraduate and Master’s degrees, both in electrical engineering, from the PES Institute of Technology, India and the Indian Institute of Science, India in 2011 and 2013 respectively. During 2011-2013, she was also an intern in the Electromechanical Control Systems lab at GE Global Research, Bangalore. Sivaranjani’s research interests are in the area of distributed control for large-scale infrastructure networks, with emphasis on power grids and transportation networks. She is a recipient of the prestigious and selective international Schlumberger Foundation Faculty for the Future fellowship and the Zonta International Amelia Earhart fellowship. She is also a Notre Dame NSF Ethical Leaders in STEM fellow for the year 2016-17. Host: Le Xie

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