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1. Dynamic Placement in Refugee Resettlement

   https://doi.org/10.1145/3465456.3467534  

   Ahani, Narges; Gölz, Paul; Procaccia, Ariel D.; Teytelboym, Alexander; Trapp, Andrew C. (January 2021, 22nd ACM Conference on Economics and Computation Proceedings.)

   null (Ed.)

   Employment outcomes of resettled refugees depend strongly on where they are placed inside the host country. While the United States sets refugee capacities for communities on an annual basis, refugees arrive and must be placed over the course of the year. We introduce a dynamic allocation system based on two-stage stochastic programming to improve employment outcomes. Our algorithm is able to achieve over 98 percent of the hindsight-optimal employment compared to under 90 percent of current greedy-like approaches. This dramatic improvement persists even when we incorporate a vast array of practical features of the refugee resettlement process including indivisible families, batching, and uncertainty with respect to the number of future arrivals. Our algorithm is now part of the Annie™ MOORE optimization software used by a leading American refugee resettlement agency. The full version of this paper is available at https://arxiv.org/pdf/2105.14388.pdf. 

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2. Placement Optimization in Refugee Resettlement

   https://doi.org/10.1287/opre.2020.2093  

   Ahani, Narges; Andersson, Tommy; Martinello, Alessandro; Teytelboym, Alexander; Trapp, Andrew C. (March 2021, Operations Research)

   null (Ed.)

   Every year, tens of thousands of refugees are resettled to dozens of host countries. Although there is growing evidence that the initial placement of refugee families profoundly affects their lifetime outcomes, there have been few attempts to optimize resettlement decisions. We integrate machine learning and integer optimization into an innovative software tool, Annie™ Matching and Outcome Optimization for Refugee Empowerment (Annie™ Moore), that assists a U.S. resettlement agency with matching refugees to their initial placements. Our software suggests optimal placements while giving substantial autonomy to the resettlement staff to fine-tune recommended matches, thereby streamlining their resettlement operations. Initial back testing indicates that Annie™ can improve short-run employment outcomes by 22%–38%. We conclude by discussing several directions for future work. 

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3. The problem of the future in the spacetime of resettlement: Iraqi refugees in the U.S.

   https://doi.org/10.1177/02637758221088865  

   Secor, Anna J; Ehrkamp, Patricia; Loyd, Jenna M (June 2022, Environment and Planning D: Society and Space)

   How do the lost futures of forced displacement converge with the impasse of being resettled to a “post-future” society such as the U.S.? Based on interviews conducted between 2016 and 2019 with resettlement agents, service providers and Iraqis resettled in the U.S., we argue that the condemnation of “expectations” (that is, realistic hope) coupled with the demand for refugees’ gratitude means that Iraqis resettled to the U.S. are asked to sustain a “hope against hope” for the fullness of American futurity, even in the face of its collapse. We argue that this prescribed structure of feeling distorts the affective realities of those for whom resettlement has meant at once the loss of past futures (e.g. professional qualifications, career trajectories, social status, or intergenerational cycles of care) and the running aground of capacities for futurity – especially as these capacities are bound up with transnationally stretched and reconfigured familial relations. What is at stake is the recognition of the crisis of futurability in the spacetime of resettlement and the rightfulness of refugee expectations for a more humane and fulfilling resettlement. 

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4. Gendered, Collectivist Journeys: Exploring Sociotechnical Adaptation Among Afghan Refugees in the USA

   https://doi.org/10.1145/3687037  

   Batool, Amna; Dillahunt, Tawanna R; Hui, Julie; Naseem, Mustafa (November 2024, Proceedings of the ACM on Human-Computer Interaction)

   This paper presents findings from an empirical study that uncovers the economic, psychological, and socio-cultural adaptation strategies used by recent Afghan refugees in a midwestern U.S. state. Through 14 semi-structured interviews conducted between February and April 2023, this study investigates how Afghan refugees utilize technology, tools, and skills in their resettlement process, and builds upon Hsiao et al.'s conceptualization of sociotechnical adaptation. The findings reveal (i) gender and collectivist cultural values play a big role in determining the types of adaptation strategies used by men versus women, (ii) strategic choices in terms of the type of support sought depending on shared versus non-shared identity of host community members, (iii) a notable tension between economic adaptation and preserving socio-cultural values is observed, and (iv) creative, collective solutions by women participants to address economic challenges, contributing to the discourse on solidarity economies in HCI. Key contributions include (a) design implications for technological products that can aid in psychological adaptation, fostering solidarity economies, and creating digital safe spaces for refugees to connect with shared-identity host populations, and (b) policy and program recommendations for refugee resettlement agencies to enhance digital literacy among refugees. 

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5. Linguistic Hooks: Investigating The Role of Language Triggers in Phishing Emails Targeting African Refugees and Students

   https://doi.org/10.56553/popets-2026-0011  

   Menon, Mythili; Vinayaga-Sureshkanth, Nisha; Schon, Alec; Hemberger, Kaitlyn; Jadliwala, Murtuza (January 2026, Proceedings on Privacy Enhancing Technologies)

   Phishing and sophisticated email-based social engineering attacks disproportionately affect vulnerable populations, such as refugees and immigrant students. However, these groups remain understudied in cybersecurity research. This gap in understanding, coupled with their exclusion from broader security and privacy policies, increases their susceptibility to phishing and widens the digital security divide between marginalized and non-marginalized populations. To address this gap, we first conducted digital literacy workshops with newly resettled African refugee populations (n = 48) in the US to improve their understanding of how to safeguard sensitive and private information. Following the workshops, we conducted a real-world phishing deception study using carefully designed emails with linguistic cues for three participant groups: a subset of the African US-refugees recruited from the digital literacy workshops (n = 19), African immigrant students in the US (n = 142), and a control group of monolingual US-born students (n = 184). Our findings indicate that while digital literacy training for refugees improves awareness of safe cybersecurity practices, recently resettled African US-refugees still face significant challenges due to low digital literacy skills and limited English proficiency. This often leads them to ignore or fail to recognize phishing emails as phishing. Both African immigrant students and US-born students showed greater caution, though instances of data disclosure remained prevalent across groups. Our findings highlight, irrespective of literacy, the need to be trained to think critically about digital security. We conclude by discussing how the security and privacy community can better include marginalized populations in policy making and offer recommendations for designing equitable, inclusive cybersecurity initiatives. 

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