NSF CAREER Award To Develop Models for Human Trafficking Interdiction and Service Provision
MIE Assistant Professor Kayse Lee Maass received a $553,946 NSF CAREER award for “Multi-Agent Network Interdiction and Service Provision Models To Counter Human Trafficking.”
Abstract Source: NSF
This Faculty Early Career Development Program (CAREER) grant will contribute to the progress of science and the advancement of national welfare by supporting research to more effectively combat human trafficking via improved understanding and disruption of the networks that enable trafficking. Despite significant efforts, current anti-trafficking interventions are often fragmented and lack coordination, limiting their effectiveness. Moreover, the success of interventions to disrupt trafficking networks and the availability of support services for survivors are deeply interconnected: access to services influences the effectiveness of interdictions which, in turn, affects the number of survivors seeking services. This project will develop novel analytical decision models to stimulate enhanced collaboration among stakeholders, address the interdependencies between interdictions and survivor services, and guide the optimal allocation of limited resources. The project emphasizes the importance of conducting research in partnership with community members and individuals with lived experience, such as trafficking survivors, to ensure the research is contextually nuanced. As such, the educational initiatives include research fellowships for trafficking survivors and training researchers on how to build and sustain community-engaged research partnerships. These efforts aim to foster a new generation of leaders equipped to address pressing societal issues.
This project intends to advance fundamental knowledge in bi-level and two-stage stochastic optimization with endogenous uncertainty while contributing to the growing field of operations engineering models focused on illicit networks. The project is structured into three key components: (1) developing a new class of multi-path network evasion interdiction models to optimize collaboration among multiple interdictors and minimize the probability of traffickers evading detection; (2) creating explainable policies to schedule survivors to services more effectively within existing capacity and determining cost-efficient ways to expand capacity to meet their needs; and (3) integrating these models into a systems framework to analyze the dynamic interplay between interdiction and survivor support, where effective interdictions increase the number of survivors needing support, and improved survivor services enhance interdiction success.