Anna Kruspe

About

Anna Kruspe is a leading researcher at the intersection of machine learning and geospatial data analysis, with a core focus on uncertainty quantification in deep neural networks. Her landmark survey, "A survey of uncertainty in deep neural networks" (2023), has garnered over 1,100 citations, establishing itself as a foundational reference for researchers grappling with the reliability of AI predictions. Kruspe’s work is distinguished by its practical impact: she has pioneered methods for applying neural networks to satellite imagery, enabling more robust environmental monitoring, disaster response, and land-use classification. By systematically addressing how deep learning models can express confidence—or lack thereof—in their outputs, she has helped bridge the gap between theoretical AI and high-stakes real-world applications. Her contributions are particularly notable for advancing trustworthy AI in domains where errors carry significant consequences, such as climate science and humanitarian aid. Through her research, Kruspe has become a key voice in making neural networks not just more powerful, but more accountable, inspiring a new generation of researchers to prioritize uncertainty as a critical dimension of model performance.

Research Focus

Key Achievements

Top Papers

1. 1
   A survey of uncertainty in deep neural networks

   1,134 citations · 2023

Key Collaborators

Contact & Links