Data-Driven and Resilient Algorithms for Autonomous Cyber-Physical-Systems | Oμιλία του Καθηγητή του Πολυτεχνείου της Virginia Κυριάκου Βαμβουδάκη | Πολυτεχνειούπολη

25.07.2017 11:18 Παλαιότητα 122 days
Κατηγορία: από Τμήμα Δημοσίων και Διεθνών Σχέσεων, Campus, Απόφοιτοι, Συνέδρια - Ημερίδες - Διαλέξεις

Data-Driven and Resilient Algorithms for Autonomous Cyber-Physical-Systems | Oμιλία του Καθηγητή του Πολυτεχνείου της Virginia Κυριάκου Βαμβουδάκη | Πολυτεχνειούπολη



Ο Καθηγητής του Πολυτεχνείου της Βιρτζίνια (Virginia Tech) και απόφοιτος του Πολυτεχνείου Κρήτης, κ. Κυριάκος Βαμβουδάκης έδωσε ομιλία με τίτλο "Data-Driven and Resilient Algorithms for Autonomous Cyber-Physical-Systems". Η ομιλία πραγματοποιήθηκε στις 25/7/2017 στο Μεγάλο Αμφιθέατρο του κτιρίου επιστημών, στην Πολυτεχνειούπολη. 

Περίληψη της ομιλίας:

Embedded sensors, computation, and communication have enabled the development of sophisticated sensing devices for a wide range of cyber-physical applications that include safety monitoring, surveillance, motion planning, search and rescue, traffic monitoring, and power systems. However, the deployment of such devices has been slowed by concerns regarding their vulnerability to both stochastic failures and cyber-physical attacks. Nowadays the efficiency will be defined by our potentials to adapt (complete autonomy) in decentralized, unknown and complex environments to enable capabilities beyond human limits. Until the achievement of near-complete autonomy, sensor technologies remain a critical issue for Unmanned Aerial Vehicle (UAV) control systems. In the first part of the talk, I will address the problem of estimating the true status of an event based on a multitude of sensors that may have been tempered by an attacker, i.e. the estimation of a binary random variable based on noisy and attacked measurements. The estimation problem is formulated as a zero-sum partial information game in which a detector attempts to minimize the probability of an estimation error and an attacker attempts to maximize this probability. A significant novelty of our approach with respect to classic problems of Byzantine faults is that we do not assume perfect sensors, i.e., even the sensors that have not been manipulated can produce incorrect results, which is common in the network-security domain. In the second part of the talk, I will use techniques from approximate dynamic programming and learning to design a new family of model-free plug-n-play autonomous control algorithms to mitigate cyber-physical attacks and faults. These algorithms will converge online, in real time to game-theoretic solutions even when attacked by persistent adversaries including jammers. The proposed approaches combine networked feedback control, game theory, network security, reinforcement learning, and serve as a tool for approaching difficult problems that without learning-based approaches are hard or impossible to solve.

Σύντομο βιογραφικό:

Kyriakos G. Vamvoudakis was born in Athens, Greece. He received the Diploma in Electronic and Computer Engineering from Technical University of Crete, Greece in 2006 with highest honors. After moving to the United States of America, he studied at The University of Texas with Frank L. Lewis as his advisor and he received his M.S. and Ph.D. in Electrical Engineering in 2008 and 2011 respectively. From May 2011 to January 2012, he was working as an Adjunct Professor and Faculty Research Associate at the University of Texas at Arlington and at the Automation and Robotics Research Institute. During the period from 2012 to 2016 he was a project research scientist at the Center for Control, Dynamical Systems and Computation at the University of California, Santa Barbara. He currently serves as an Assistant Professor at the Kevin T. Crofton Department of Aerospace and Ocean Engineering (AOE) at Virginia Tech. His research interests include approximate dynamic programming, game theory, and optimal control. Recently, his research has focused on cyber-physical security, networked control, smart grid and multi-agent optimization. Dr. Vamvoudakis is the recipient of several international awards including the 2016 International Neural Network Society Young Investigator (INNS) Award, the Best Paper Award for Autonomous/Unmanned Vehicles at the 27th Army Science Conference in 2010, the Best Presentation Award at the World Congress of Computational Intelligence in 2010, and the Best Researcher Award from the Automation and Robotics Research Institute in 2011. He is a member of Tau Beta Pi, Eta Kappa Nu and Golden Key honor societies and is listed in Who's Who in the World, Who's Who in Science and Engineering, and Who's Who in America. He has also served on various international program committees and has organized special sessions for several international conferences. He currently is a member of the Technical Committee on Intelligent Control of the IEEE Control Systems Society (TCIC), a member of the Technical Committee on Adaptive Dynamic Programming and Reinforcement Learning of the IEEE Computational Intelligence Society (ADPRLTC), an Associate Editor of the Journal of Optimization Theory and Applications, an Associate Editor on the IEEE Control Systems Society Conference Editorial Board, an Editor in Chief of the Communications in Control Science and Engineering, a registered Electrical/Computer engineer (PE) and a member of the Technical Chamber of Greece. He is a Senior Member of IEEE.


© Πολυτεχνείο Κρήτης 2012
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