Home Chang Liu Chang Liu Building damage estimation after natural disaster using multi satellite source data based on machine learning UNSW Sydney Chang Liu is a PhD candidate in Surveying and Geospatial Engineering at the University of New South Wales (UNSW) Sydney. She completed a Bachelor of Civil Engineering degree at University of Science and Technology Beijing (USTB) and a Master of Philosophy in Built Environment at UNSW Sydney. Her research is focused on data semantic segmentation for building damage assessment using artificial intelligence methods with 2D satellite images and 3D LiDAR point cloud. She received ‘Best Poster’ award of SmartSat CRC Conference 2022. She also worked as a UNSW demonstrator for multiple courses. In addition to research and teaching, she has demonstrated her strong leadership and excellent communication and teamwork skills as the vice-president of Civil and Environment Engineering Research Student Association (CERSA) at UNSW Sydney. CERSA aims at connecting students across the school by organizing various events that promote social gatherings and provide a healthy working environment. Project title: Building damage estimation after natural disaster using multi satellite source data based on machine learning Publications Dielectric Fluctuation and Random Motion over Ground Model (DF-RMoG): An Unsupervised Three-Stage Method of Forest Height Estimation Considering Dielectric Property Changes Bibliometric Analysis of Interferometric Synthetic Aperture Radar (InSAR) Application in Land Subsidence from 2000 to 2021 A Novel Attention-based Deep Learning Method for Post-disaster Building Damage Classification Channel Attention and Normal-Based Local Feature Aggregation Network (CNLNet): A Deep Learning Method for Predisaster Large-Scale Outdoor Lidar Semantic Segmentation The Influence of Changing Features on the Accuracy of Deep Learning-Based Large-Scale Outdoor Lidar Semantic Segmentation