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Michael Gabbay

Senior Principal Physicist






Dr. Gabbay's current research involves the development of mathematical models and computational simulations of network dynamics, focusing on social and political systems. He has also conducted research in the areas of nonequilibrium pattern formation, coupled oscillator dynamics, sensor development, and data analysis algorithms. His work has appeared in physics, engineering, biology, and political science publications. Dr. Gabbay received a B.S in physics from Cornell University and a Ph.D. in physics from the University of Chicago with a specialization in nonlinear dynamics.


2000-present and while at APL-UW

Social network analysis in the study of terrorism and insurgency: From organization to politics

Zech, S.T., and M. Gabbay, "Social network analysis in the study of terrorism and insurgency: From organization to politics," Int. Stud. Rev., 18, 214-243, doi:10.1093/isr/viv011, 2016.

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1 Jun 2016

Research using social network analysis to study terrorism and insurgency has increased dramatically following the 9/11 attacks against the United States. This research emphasizes the importance of relational analysis and provides a variety of concepts, theories, and analytical tools to better understand questions related to militant group behavior and outcomes of terrorism and insurgent violence. This paper defines key network concepts, identifies important network metrics, and reviews theoretical and empirical research on network analysis and militant groups. We find that the main focus of existing research is on organizational analysis and its implications for militant group operational processes and performance. Few studies investigate how differences in network structure lead to divergent outcomes with respect to political processes such as militant group infighting, their strategic use of violence, or how politically salient variables affect the evolution of militant cooperative networks. Consequently, we propose a research agenda aimed at using network analysis to investigate the political interactions of militant groups within a single conflict and provide illustrations on how to pursue this agenda. We believe that such research will be of particular value in advancing the understanding of fragmented civil wars and insurgencies consisting of multiple, independent militant groups.

Data processing for applications of dynamics-based models to forecasting

Gabbay, M., "Data processing for applications of dynamics-based models to forecasting," in Sociocultural Behavior Sensemaking: State of the Art in Understanding the Operational Environment, J.E. Egeth, G.L. Klein, and D. Schmorrow, eds., 245-268 (McLean, VA: The MITRE Corporation, 2015).

1 Jan 2015

Majority rule in nonlinear opinion dynamics

Gabbay, M., and A.K. Das, "Majority rule in nonlinear opinion dynamics," in International Conference on Theory and Application in Nonlinear Dynamics (ICAND 2012), edited by V. In, A. Palacios, and P. Longhini, 167-179, doi:10.1007/978-3-319-02925-2_15 (Switzerland: Springer International, 2014).

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1 Jan 2014

Using a nonlinear model of opinion dynamics on networks, we show the existence of asymmetric majority rule solutions for symmetric initial opinion distributions and symmetric network structure. We show that this occurs in triads as the result of a pitchfork bifurcation and arises in both chain and complete topologies with symmetric as well as asymmetric coupling. Analytical approximations for bifurcation boundaries are derived which closely match numerically-obtained boundaries. Bifurcation-induced symmetry breaking represents a novel mechanism for generating majority rule outcomes without built-in structural or dynamical asymmetries; however, the policy outcome is fundamentally unpredictable.

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Acoustics Air-Sea Interaction & Remote Sensing Center for Environmental & Information Systems Center for Industrial & Medical Ultrasound Electronic & Photonic Systems Ocean Engineering Ocean Physics Polar Science Center