Overview
Katelyn covers AI applications in animal behavior and welfare, exploring how artificial intelligence is transforming wildlife research and animal care. Her recent work examines cross-species emotion detection through AI analysis of vocalizations—research she sees as supporting rather than replacing human observation in behavior science and welfare work.
Key Themes
- Wildlife Research
- Animal Behavior Analysis
- Emotion Detection
- Species Identification
- Animal Health Tech
Posts
Covers University of Copenhagen research showing machine learning can distinguish positive and negative emotional states in ungulate vocalizations with 90% accuracy—"a huge step toward tools that could support, rather than replace, human observation."
Addresses AI applications in understanding wildlife behavioral patterns through advanced monitoring systems.
Focuses on improving species identification capabilities through AI-powered field tools.
Examines the commercial growth potential within the AI-driven animal health technology sector.