|Other - Colloquium on Artificial Intelligence Research and Optimization|
|Scaling Geospatial Artificial Intelligence: Opportunities and Challenges|
|H. Lexie Yang, Oak Ridge National Laboratory|
|Lead Staff Scientist|
|Virtual- Details TBD Zoom
May 19, 2021 - 01:00 pm
The increasing accessibility of geospatial imagery and rapid advances in AI continues to drive a surge in adaptation of GeoAI systems. From mapping to real-time monitoring and solving long-standing geoscience problems, GeoAI plays a critical role to revolutionizing how geospatial data can be transformed into actionable knowledge in our daily life. While holding great promise, the tremendous amount of imagery describing the surface of the Earth every day entails the challenges of collecting, refining, analyzing, and curating those data. These challenges necessitate the need of integrating advances in computing technologies to deliver the actionable geo-knowledge with scalable approaches.
H. Lexie Yang is a Lead staff scientist in GeoAI Group at Oak Ridge National Laboratory. Her research interests focus on advancing high performance computing and machine learning approaches for geospatial data analysis. She had collaborated with esteemed scholars for NASA AIST, NSF, DOE sponsored projects and currently leads several AI-enabled geoscience data analytics projects with large-scale multi-modality geospatial data. The recent work from her team has been widely used to support national-scale disaster assessment and management by agencies. She received PhD in Civil Engineering from Purdue University in 2014.