Ribana Roscher

Papers

Total Citations

1,138

H-Index

About

Ribana Roscher is a distinguished researcher whose work bridges the fields of machine learning, uncertainty quantification, and digital agriculture. Based at the University of Bonn, she has made significant contributions to the intersection of deep learning and real-world applications, particularly in remote sensing and agricultural sciences. Her most influential work includes a comprehensive survey on uncertainty in deep neural networks (2023), which has garnered an impressive 1,134 citations, reflecting its foundational importance to researchers and practitioners grappling with the reliability of AI systems. This contribution addresses a critical challenge: as neural networks permeate scientific disciplines and real-world applications, understanding and quantifying their confidence levels becomes essential for responsible deployment. Roscher also champions data-centric approaches to precision agriculture, advocating for the integration of data science, machine learning, sensor technologies, and robotics to address global demands for food, feed, fiber, and fuel while minimizing environmental impact. Her perspective on digital agriculture positions her as a forward-thinking voice in sustainable technological innovation. Through her dual expertise in trustworthy machine learning and intelligent agricultural systems, Roscher has established herself as a valuable contributor to both theoretical foundations and pressing societal challenges of our time.