Project Archive

Develops next‑generation optical sensors with onboard AI/ML to capture real‑time data on prescribed fire behavior, energy, and smoke emissions. Addresses how fire dynamics and resulting smoke affect individuals and communities, filling critical knowledge gaps in prescribed fire usage.

Uses drone‑collected aerial imagery and machine learning to interpret large, complex datasets for science questions related to snow‑water resources, wildfire management, and abandoned oil well monitoring. Supports natural‑resource decision‑making by generating processed data that helps test hypotheses and improve assessments of snowpack, fire behavior, and environmental hazards.

Studies how contaminants from hard rock mining, intensive agriculture, and energy extraction affect Montana’s water quality across three representative watersheds. Brings together researchers in molecular science, engineering, environmental science, sensors, and social science to understand contaminant origins, transformations, and impacts on ecosystems and communities.

Proposal Title: Microbial processes of pelagic anaerobic methane cycling in oxygen minimum zones. Studies how microorganisms in deep and extreme environments produce and consume methane, using sites like the Sanford Underground Research Facility and Yellowstone National Park as testbeds. Develops genome‑to‑phenome tools to harness novel methane‑metabolizing microbes for potential applications such as biofuels, biopolymers, and clean energy technologies.