Max carried out his PhD in our group between 2018 and 2024, defending his thesis (Dr. rer. nat.) in July 2024. His doctoral research developed and applied machine learning and deep learning methods for ecological inference — from joint species distribution models that scale to large community datasets to predicting trait matching in ecological networks. Over the course of his PhD he also authored several widely used R packages, including cito (externer Link, öffnet neues Fenster) for training neural networks in R and s-jSDM (externer Link, öffnet neues Fenster) for fast, scalable joint species distribution modeling.
Since completing his doctorate, Max has remained in the Theoretical Ecology chair as a postdoctoral researcher and, since 2025, has led his own research group within the chair. His group investigates how artificial intelligence — in particular deep and machine learning — can be used to study ecological systems such as bipartite networks and biodiversity patterns, including the development of AI-based insect monitoring in the bAImo project (externer Link, öffnet neues Fenster).
Congratulations, Max! A well-deserved recognition of an excellent thesis!
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Dr. Maximilian Pichler
Ecological Machine Learning Group
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