Research Centers & Labs

We merge animal tracking, remote sensing, and intensive field research to gain insights into the resource and habitat requirements of wildlife. We also assess emerging threats to critical habitats and work to understand the impacts of habitat change on wildlife behavior and populations.

We work at the intersection of disease ecology, population demography, and animal behavior, often employing data science techniques to provide evidence-based solutions to conservation challenges. We also study disturbance ecology, particularly how natural and anthropogenic disturbances influence host-pathogen dynamics.

The Field Lab is an interdisciplinary research group dedicated to applying computational and data-driven approaches to complex questions about the human past and present. The lab’s core research integrates remote sensing, data science, and machine learning to investigate patterns of human settlement, mobility, and environmental change across both archaeological and contemporary landscapes.

The Human-Environmental Systems Lab led by Dr. Jake Hawes addresses the challenge of planning and designing systems to be more resilient to natural hazards and in sync with natural and social systems. We are interdisciplinary scholars of coupled human-environmental systems, drawing on theory and methods from planning, geography, and engineering. The lab deploys computing both as a research tool and a research subject, with projects ranging from spatial optimization of local food-energy-water systems to examinations of residents' perspectives on AI's role in rural areas.

The Joyce Lab specializes in the application of high-performance computing, statistics, and data science techniques to problems in stellar astrophysics, especially stellar structure and evolution, stellar variability, and Galactic archaeology. 

The Koger Lab specializes in designing and using novel imaging and image processing techniques to study natural systems. The lab uses a combination of drone, satellite, and ground-based imagery paired with deep learning detection and tracking algorithms to investigate how animals’ behaviors are influenced by their social and physical environments. The labs current research program is focused on novel methods for monitoring landscapes in the American West and understanding collective navigation and predator-prey dynamics in Pacific salmon ecosystems around Bristol Bay, Alaska.

Changing natural disaster risk profiles are already rippling across financial markets and wreaking havoc to ecosystems the human-built environment, disproportionately affecting under-resourced communities. Studying the underpinning atmospheric physical mechanisms which modulate these risks is hampered by the carse resolution (grid lengths of >100 km) of earth system models (ESMs), which are the principle tools used explore how the earth system's varying components (cryosphere, atmosphere, ocean, land-surface, vegetation) interconnect to modulate our day-to-day weather.

The Taylor Lab develops network-based models for complex systems including social, biological, physical, and technological applications including AI applications and algorithm development. Projects range from mathematical modeling and theoretical derivations to applied studies in close collaboration with domain experts.
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Our lab focuses on geospatial machine learning and spatiotemporal data science to understand human–environment systems. We investigate population mobility and regional dynamics using computational methods, including neural networks, spatial modeling, and large-scale geospatial data integration. Our work supports applications in rural systems, public health, tourism, and transportation, helping inform community planning and policy.