Research by Status & Date

Signals for Understanding Wyoming Water and Fire Futures

Lays the groundwork for community-based hazard planning in Wyoming's Wind River Basin through literature synthesis, coalition building, and theory development around 'signals committees' — bodies that bring together scientific data, community knowledge, and traditional ecological knowledge to identify the conditions that should trigger adaptation responses. The longer-term goal is a sustained, community-grounded planning infrastructure for navigating water and fire futures under climate change.

AI for Wyoming, By Wyoming

Wyoming is rapidly becoming a testing ground for AI infrastructure — data centers, smart agriculture, AI-assisted governance — yet rural residents have had little say in how these technologies arrive or what they displace. This project surveys Wyomingites' understanding of and concerns about AI, using speculative narratives and mixed methods to surface authentic community perspectives and build an evidence base for human-centered, rural-values-aligned AI development across the state.

Inventory and Evaluation of Operational Fire Potential Forecasts Across Scales for Decision Support

Wildfire managers rely on dozens of fire potential forecast products to guide decisions — but these tools have never been systematically cataloged or independently evaluated. This project builds a standardized, open-access inventory of existing fire potential forecast products and conducts rigorous evaluation of selected tools using the METplus verification framework, with the goal of giving practitioners clear, evidence-based guidance on which products are most reliable, under what conditions, and at what scales.

Digital Twin Readiness and Equity in Small Cities

Investigates whether digital twin technology deepens or reduces inequality in small cities, combining a critical literature review on digital twin equity with a comparative empirical assessment of data infrastructure and governance readiness in Laramie and Afton, Wyoming. The work produces a replicable framework for evaluating digital twin readiness in resource-constrained communities — asking whether the technology can serve small cities equitably, or whether it reproduces the 'smart urban divide' it promises to bridge.

AI-Optimized Controlled Environment Agriculture

Applies AI planning methods to optimize the energy use and carbon footprint of controlled environment agriculture (CEA) operations, treating the scheduling of lighting, heating, and water systems as an optimization problem that responds dynamically to grid prices, fuel mix, and weather conditions. A second phase extends this model spatially, identifying where in the Mountain West CEA is best positioned to take advantage of expanding renewable energy capacity while minimizing costs and environmental impact.

The Geography of Social Vulnerability and Wildfire Risk across Wyoming

Develops a Wyoming-specific social vulnerability index and maps it against wildfire hazard across the state's 23 counties and 132 census tracts, using local Census data and expert elicitation to capture dimensions of vulnerability that national indices like the CDC/ATSDR SVI systematically undercount in rural, resource-dependent contexts. The goal is to identify where social vulnerability and fire risk most dangerously overlap — and to give policymakers, emergency managers, and community leaders geographically targeted evidence for mitigation investment.

Digital Twins for Smart Rural Places

Develops digital twin frameworks for infrastructure and services in small towns and rural communities across Wyoming, using Laramie and Afton as testbed communities. The work combines smart sensing, data integration, and computational modeling to create living simulations that help community planners and managers understand system behavior, anticipate problems, and make better-informed decisions about local infrastructure.

The Impact of Wildfire Smoke on Tourism in the GYE

Examines how increasing wildfire smoke events are affecting tourism in the Greater Yellowstone Ecosystem — one of the most visited landscapes in the United States — using climate projections and economic data to estimate current and future impacts on visitation, recreation, and gateway community livelihoods.

ARCAP — Alaska Railbelt Critical Assets Project

Examines critical infrastructure resilience across Alaska's Railbelt region — the interconnected corridor of communities, utilities, and supply networks stretching from Fairbanks to the Kenai Peninsula. A central focus is the Port of Alaska, a single point of failure for the entire state's supply chain, analyzed through infrastructure assessment, expert elicitation, and tabletop exercises to understand cascading vulnerabilities and inform mitigation investment.

Stylized Facts for the Circular Economy

An international synthesis effort distilling the circular economy literature into a set of empirically grounded 'stylized facts' — concise, evidence-based propositions that capture what is reliably known about CE systems. The goal is to make the state of CE knowledge accessible and actionable for policymakers, practitioners, and researchers who need to navigate a sprawling and often contradictory literature.

Assessing Gentrification in Michigan's Coastal Communities

Produces the first systematic map of blue gentrification across 46 of Michigan's Great Lakes coastal communities, using household-level spatial analysis to track how waterfront proximity has driven changes in property values, wealth, and residential displacement between 2006 and 2020. A central question is whether Great Lakes Restoration Initiative (GLRI) waterfront revitalization investments have paradoxically accelerated displacement in the communities they were meant to benefit. Findings are translated into a publicly accessible MI Blue Gentrification Hotspot Tool and policy brief aimed at local, state, and federal decision-makers.

AI Best Practices for Industrial Ecology

Two parallel papers examine the state of machine learning in industrial ecology from complementary angles. Rankin et al. audits reproducibility across ML studies in the field, finding that best practices for transparency and replication are rarely followed. Taghdisian et al. takes a broader evaluative lens, assessing how, when, and in what ways AI is being applied well or poorly across IE research.

Coupled Hazard Modeling for Rural and Gateway Communities

Develops coupled modeling approaches that link wildfire dynamics, atmospheric processes, and human social systems to understand how disturbance events affect rural and gateway communities in the Greater Yellowstone Ecosystem and across Wyoming. The work aims to improve the scientific basis for anticipating how cascading hazards unfold across landscapes and communities — and to translate that understanding into scenario planning and decision-support tools for managers and planners facing an increasingly dynamic fire environment.

GLO-FORCE: Urban Food Systems Resilience

Integrates blockchain, AI, and geospatial intelligence to strengthen food supply chain resilience in urban regions, with plans to pilot in St. Louis using the 2025 EF3 tornado as a real-world stress test case. The project aims to identify vulnerabilities in local food distribution and emergency response networks and develop decision-support tools for rapid recovery after disruption. Seeking funding — reach out to Jake.

Urban Symbiosis

Developed and empirically grounded the concept of urban symbiosis — the mutually beneficial, citizen-led sharing of materials and resources within cities. A London case study found that social and wellbeing outcomes frequently outweigh environmental motivations, challenging purely resource-efficiency framings of the circular economy.

FEW-Meter

Measured the food, energy, and water flows of urban farms across five countries in Europe and North America, establishing a rigorous empirical foundation for evaluating the environmental performance of urban agriculture. The project developed and applied a standardized accounting methodology — the FEW-Meter tool — to enable cross-site comparison at a scale not previously attempted in the field.