Saurabh Amin, Associate Professor, MIT
This talk presents a prescriptive analytics framework for designing inspection and response operations of service utilities facing risks of natural disasters and security attacks. In the first part of the talk, we introduce a stochastic orienteering and network probing problem for localizing failures in the aftermath of a major natural disaster. We develop a predictive model for failure localization using data from inspection operations of a real-world natural gas pipeline network. Next, we exploit the problem structure to design a scalable non-adaptive algorithm based on integer programming. Our results lead to practical and efficient strategies for disaster response operations. In the second part of the talk, we consider the problem of monitoring vulnerable network components with the minimum number of smart detectors against multiple random or adversarial disruptions. This network inspection problem can be formulated as a mathematical program with constraints involving Nash equilibria of a large-scale strategic game. We develop a scalable approach that computes randomized monitoring strategies based on solutions of a minimum set cover problem and a maximum set packing problem, along with optimality guarantees. We demonstrate that the proposed framework effectively utilizes the available network data to improve the resilience of critical infrastructures against a broad class of failures. The first part is joint work with Mathieu Dahan and Georgia Perakis, and the second part is joint work with Mathieu Dahan and Lina Sela.
Dr. Saurabh Amin, Associate Professor in the Department of Civil and Environmental Engineering at MIT, will present a seminar on Analytics-Driven Operations for Critical Infrastructure Resilience. Dr. Amin is Robert N. Noyce Career Development Associate Professor in the Department of Civil and Environmental Engineering at MIT. He is also affiliated with the Institute of Data, Systems and Society and the Operations Research Center at MIT. His research focuses on the design of network inspection and control algorithms for infrastructure systems resilience. He studies the effects of security attacks and natural events on the survivability of cyber-physical systems, and designs incentive mechanisms to reduce network risks. Dr. Amin received his Ph.D. from the University of California, Berkeley in 2011. His research is supported by NSF CPS FORCES Frontiers project, NSF CAREER award, Google Faculty Research award, DoD-Science of Security Program, and Siebel Energy Institute Grant.