Much of my work emphasizes interdisciplinary collaboration and community-engaged research, including projects related to Tribal environmental data sovereignty, Earth data science infrastructure, and educational access to computational tools. I believe strongly that environmental data science should not only produce rigorous analyses, but also support transparency, accessibility, and local decision-making capacity.

In addition to my environmental research, I maintain a strong interest in systems thinking, simulation, games, and puzzle-based learning. Many of the same concepts that govern environmental systems also appear in games and computational simulations. I enjoy exploring these overlaps through open-source projects, educational tools, and experimental modeling workflows.

My teaching philosophy emphasizes curiosity, exploration, and reproducibility. I aim to create learning environments where students can engage directly with real-world datasets, computational thinking, and systems-based approaches to environmental challenges.

Residuals as signal: Revealing hidden environmental drivers and data gaps in sensor-poor landscapes through remote sensing models