Nico Lang

Nico Lang is an Assistant Professor at the University of Copenhagen's Department of Computer Science, associated with the Pioneer Centre for AI and Global Wetland Centre. He holds a PhD from ETH Zurich where he developed methods for global forest structure mapping. His research bridges computer vision, machine learning, and remote sensing to address environmental challenges like deforestation monitoring and climate change mitigation.

Lang's research focuses on:

• Developing probabilistic deep learning models for global canopy height estimation
• Advancing open-set recognition under adversarial conditions
• Creating multi-modal representation learning frameworks for geospatial data
• Applying computer vision to biodiversity monitoring and conservation

His work frequently appears in top venues like Nature, CVPR, and ECCV.

His publications show strong emphasis on: environmental applications of AI, uncertainty-aware deep learning, and global-scale geospatial analysis. Recent work explores vision-language models and fine-grained open-set recognition.

Awards & Honors:

• Culmann Prize for outstanding doctoral thesis (2023)
• Outstanding Reviewer for CVPR 2023
• U.V. Helava Award for best paper in ISPRS Journal (2019)
• Associate PhD Fellow at Max Planck ETH Center (2018)

Collaborations & Labs: Directs research at the intersection of computer vision and environmental science. Key affiliations include NASA GEDI mission, Swiss Federal Institute for Forest, Snow and Landscape Research, and the Pioneer Centre for AI. Organizes workshops like FGVC at CVPR and SSL4EO summer schools.