Project title: Scaling AI for ethology and wildlife conservation
PI: Andrew Zisserman
Large-scale and long-term data on wild animals are critical for understanding behaviour and evolution. Researchers are increasingly reliant on audiovisual data collection, but major processing bottlenecks limit its full potential. This project will develop new AI tools and frameworks for modelling populations in the wild—tracking demography, behaviour, and processes such as cultural learning—at scale. By advancing methods for real-world field environments, this research aims to develop critical tools for biology and conservation, while also opening new directions for AI inspired by biological evolution and natural intelligence
