College of Computer Science and Engineering
Systems Engineering Department
Presents a Seminar on
A Modeling and Mitigation Approach for the Rising Interdependencies between Critical Infrastructures
Date: Monday, 7th December, 2020
Time: 20:00 pm (KSA Time)
Location: ZOOM Click here to join
Ahmed A. Mohamed (El-Tallawy)
Department of Electrical Engineering
City College of the City University of New York (CUNY)
Improving the protection and resilience of critical infrastructures (CIs) against natural disasters and manmade threats is an imperative short-term goal worldwide. Three highly interdependent CIs are the focus of this research: electric power systems, information and communication technologies (ICT), and electricity- based vehicles/transportation (e-transportation). Network modeling of failure modes and propagation is needed by managers to devise strategies that mitigate the impact of failures across interdependent CIs. Although much progress has been made in network modeling of CIs to date, these efforts fail to capture the complexity of CIs, are based on inadequate or inaccurate assumptions, neglect interdependencies, and are mostly empirical and statistically driven rather than based on principles of physics. The objective of this research is to improve failure and resilience modeling of interdependent CIs. This work will then be expanded using reinforcement learning to aid in decision-making. The outcome will be a framework to account for CI interdependencies that are critical for failure and disaster planning and recovery. An influence graph-based model along with a reinforcement learning-based interdependency mitigation framework have been proposed, which eloquently address a key problem that has long challenged city/infrastructure planners and operators: how to model, forecast, and prevent cascaded failures that propagate through multiple critical infrastructures. Current approaches lack accuracy and the ability to handle complexities and interdependencies. This work applies detailed physics-based bottom-up modeling coupled with the innovative application of reinforcement learning to provide a transformative advancement to the field, resulting in a more flexible and accurate analysis methodology for use in CI design, management, disaster planning, and recovery.
Ahmed Ali A. Mohamed (El-Tallawy) is an Associate Professor of Electrical Engineering (EE) at the City College of the City University of New York (CUNY). He is the EE PhD Program Advisor, and the director of the CUNY Smart Grid Interdependencies Laboratory (http://smartgrid.ccny.cuny.edu). Prof. Mohamed received his Ph.D. degree in Electrical and Computer Engineering from Florida International University in 2013. His research work is supported through funds from various companies and national funding agencies, e.g. the US National Science Foundation and New York State Energy Research and Development Authority. His research interests include critical infrastructure interdependencies, smart grid resilience, microgrids, and transportation electrification. He has numerous publications in these fields as book chapters, and articles in premier journals and conference proceedings. Prof. Mohamed is the recipient of the 2019 NSF CAREER Award, among several other honors and awards. Several of Prof. Mohamed's papers received prestigious awards. Prof. Mohamed served on review panels for several national and international funding agencies, e.g. the US Department of Energy, the US National Science Foundation and the Chilean National Science and Technology Commission. He is a Senior Member of IEEE, and has held several IEEE executive positions.
All faculty, researchers and graduate students are invited to attend.
Systems Engineering Department, College of Computer Sciences and Engineering
Telephone: +966 (13) 860 2988, Email: email@example.com, Website: www.kfupm.edu.sa/departments/se/
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