Deep learning of behavior
F. Rose Lab
University of Bonn

With a strong foundation in computational biology, data processing, and machine learning, I am passionate about unraveling the intricate relationship between animal behavior and neural activity. As the fields of Biology and Medical Sciences experience an explosion of data generation, I find it thrilling to address the growing demand for advanced data analysis and push the boundaries of scientific understanding. The rise of more powerful, flexible, and generalizable deep learning models presents exciting new opportunities.

My research focuses on developing innovative deep learning methods to connect animal movement with neural activity, leveraging unsupervised and transfer learning techniques to reduce reliance on manual labeling. I am particularly interested in exploring how biological perturbations—genetic, pharmacological, and social—influence behavior, with the ultimate goal of creating a comprehensive framework to deepen our understanding of behavioral dynamics.

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With an academic background spanning machine learning, medical imaging, and neuro biomechanics, I oriented my learning path toward exploring the rich behavioral insights both environmental and internal that the body can provide. The group's focus on connecting animal behavior with complex neural activity aligns with my drive to develop computational tools that allow us to more sensibly perceive, quantify, and understand our ecosystem.

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As a Bachelor's student in Quantitative Biology, I have noticed that one of the great qualities of a classical biologist, is the ability to be observant. For centuries, studies of animal behaviour have relied making careful observations in the wild. However, with the rate of data acquisition now greatly outpacing our ability to extract valuable information, it has become increasingly important to develop new computational methods which enable more rapid data analysis. I am therefore happy to be in an environment where I can contribute to this and learn so much along the way!

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I am a Master's student in the OEP Biology program at the University of Bonn with a strong interest in understanding why animals behave the way they do. My interest began during a behavioral ecology course, where I spent many hours observing gammarids, and it grew even stronger in my Animal Behavior seminar. I became fascinated not only by what animals do, but also by how their brains make the decisions behind those behaviors, especially in free-living animals.
This curiosity led me to join the Rose Lab, where I work on using deep learning to classify sleep stages in calves by adapting methods originally developed for humans. I enjoy combining animal behavior, neuroscience, and modern data science, and I hope my work will contribute to a better understanding of animal cognition and behavior.

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