GeoAI for Earth Observation Imagery

Dalton Lunga

Dalton Lunga is a group leader for GeoAI and a senior R&D staff scientist at ORNL. He is also an Associate Editor for Geoscience and Remote Sensing Letters. He is an interdisciplinary scientist with expertise in artificial intelligence, computer vision, high-performance computing, and remote sensing. Dalton leads multidisciplinary teams and projects focused on developing novel methods at the intersection of AI, computer vision, and geography toward the built and physical environment mapping using earth observation data. His research is impacting the generation of accurate population estimates and information about urban growth and decline, informing disaster response, and identifying at-risk areas to support national security application challenges. Prior to ORNL, Dalton was a Team Lead and Senior Research Scientist at the Council for Scientific and Industrial Research, South Africa, where he established and led a Data Science for Decision Impact team. He received his Ph.D. in Electrical and Computer Engineering from Purdue University, West Lafayette.

Ronny Hänsch

Ronny Hänsch is a scientist at the Microwave and Radar Institute of the German Aerospace Center (DLR), where he leads the Machine Learning Team in the Signal Processing Group of the SAR Technology Department. His research interests include computer vision and machine learning, with a focus on remote sensing (in particular SAR processing and analysis). He was chair of the GRSS Image Analysis and Data Fusion (IADF) technical committee from 2021-2023 and serves as co-chair of the ISPRS working group on Image Orientation and Sensor Fusion. He is editor-in-chief of Geoscience and Remote Sensing Letters and an associate editor for the ISPRS Journal of Photogrammetry and Remote Sensing. He has organized the CVPR Workshop EarthVision (2017-2024) and the IGARSS Tutorial on Machine Learning in Remote Sensing (2017-2024). He has extensive experience in organizing remote sensing community competitions, such as SpaceNet and the GRSS Data Fusion Contest.