Los Alamos National Laboratory
Advancing Machine Learning and Machine Vision Using Topological Graph-Based Representations, Methods, and Algorithms
Dr. Yang is currently a Postdoctoral Research Associate at Los Alamos National Laboratory (LANL), and will become an Assistant Professor of Geographic Information Science and and Geospatial Artificial Intelligence (GeoAI) at the University of New Mexico in January 2020. Dr. Yang received her Ph.D. in Spatial Information Science and Engineering from the University of Maine, and after that she was a Postdoctoral Researcher at Penn State University before joining LANL, where she has worked on machine learning and deep learning to analyze big geospatial data, including high resolution aerial images. Dr. Yang has worked many years at the intersection of computer science, mathematics, and geographic information science. Her multidisciplinary background on graph theory, computational geometry, and machine learning provides her a solid foundation to develop creative and novel solutions to advance computer vision tasks such as image representation, retrieval, and analysis. Dr. Yang has several top-tier journal papers in geospatial artificial intelligence, and has several accepted and published conference papers for ICCV, CVPR, and KDD workshops.