Wildlife conservation, landscape connectivity, and migration impact our society locally and globally
Species movement will accelerate with changes in land use and climate change. Management planning from a place-based, siloed approach is difficult.
The research will build fundamental insight about how different computational approaches aid methods for detecting network patterns in illicit wildlife supply chains.
This project will support national health and prosperity by developing large-scale quantitative models for the strategic design of conservation plans to preserve biodiversity.
We aim to advance machine learning techniques in order to derive useful insights from satellite imagery, at scale, with the goal of tackling pressing problems in computational sustainability.