I am a Research Scientist at the Max Planck Institute of Animal Behavior where I lead a central machine learning research group that focuses on developing advanced, general-purpose methods for the measurement and analysis of animal behavior in laboratory and field environments using computer vision, deep learning, and modern statistical methods, such as Bayesian causal inference. I work collaboratively with researchers across departments led by Martin Wikelski, Iain Couzin, and Meg Crofoot.

My research interests include how biological systems acquire and process information for making decisions. My research on insects, fish, and ungulates tests key assumptions of animal behavior at multiple scales by integrating computer vision, machine learning, information theory, and Bayesian inference. I am particularly interested in how animal collectives coordinate their movement and how individual behavior contributes to the dynamics of group-level behavior.