Research & Professional Philosophy
Community Resilience · AI for Nonprofits · Bridging Research & Practice
Community Resilience · AI for Nonprofits · Bridging Research & Practice
Community resilience and organizational resilience are fundamentally interconnected. Communities depend on the community-based organizations (CBOs) that serve them, and those organizations can only sustain their missions if they have the internal capacity to adapt and persist through disruption.
CBOs are critical anchors during disasters. They have deep local knowledge, hold institutional trust, and often remain operational when larger systems fail. At the same time, they operate under constant pressure: limited budgets, staff turnover, competing demands, and the cumulative strain of responding to recurring crises. My research investigates how hazard context (both the physical risk environment and local meaning-making around that risk) shapes what feels normal, urgent, and possible inside these organizations. Understanding these dynamics is essential to building forms of resilience that are not only theoretically sound, but workable in practice.
The nonprofit sector operates in a persistent state of resource scarcity, a condition that disasters intensify. Organizations need better tools to anticipate resource needs, plan for surges in demand, and make strategic decisions under uncertainty. Yet most community-based organizations are reactive by necessity. Even when leaders recognize the value of resilience planning, they often lack the time and capacity to build formal systems.
I am exploring how AI tools could support this work in ways that are grounded in the actual needs and constraints of CBOs. Through ongoing interviews, I find that many organizational leaders are simultaneously intrigued by AI's potential and uncertain about how to use it safely and appropriately. They see value in applications such as grant writing, communications, and administrative tasks, but they have legitimate concerns about data security, alignment with community-centered work, and the absence of organizational policies governing AI use.
Rather than imposing top-down technical solutions, my research focuses on identifying what kinds of tools would genuinely be useful to these organizations through a co-creative process rooted in lived experience. This includes exploring how predictive modeling and scenario planning could help CBOs forecast the implications of increased demand for their programs, budgets, and staffing capacity, using organizational data they already maintain (such as funding flows, staffing levels, facility costs, service delivery patterns, and historical trends).
The goal is to develop a systematic and accessible framework that helps nonprofits to plan more effectively for future disruptions without adding to their already overwhelming workload. This means building tools that integrate into existing organizational practices, that can "outlive any individual staff member," and that translate complex analytical concepts into practical, implementable systems.
My work sits at the intersection of disaster sociology, implementation science, and applied practice. I bring expertise in multilevel regression modeling, qualitative coding, participatory research design, and cross-sector coordination. I am committed to ensuring that research translates into practical impact. I focus on creating knowledge that is rigorous, accessible, and useful to the people doing the work.
Resilience requires more than good intentions. It requires infrastructure, investment, and intentional cultivation of the networks and systems that allow communities and organizations to persist through crises. My goal is to help build that infrastructure.