Research Interests

Computer vision, deep learning, and algorithms for large-scale remote sensing image and point cloud processing. Key focuses include 2D/3D vision (Graph Convolution, self-supervised learning, Transfer learning), geometric deep learning, 3D point cloud/mesh processing/NeRF.
Urban computing and environmental modeling. Key focuses include fusion of multi-source spatio-temporal geospatial data, assessment of urban infrastructure and 3D urban morphology, modeling of multi-scale human activities and sustainable interactions with the urban environment.

Grant

PI, “Research on Large-Scale Urban Building Vector Modeling Based on Deep Generative Models”, National Natural Science Foundation of China Youth Fund, 01/2025 - 12/2027
PI, “Generative 3D City Reconstruction based on Remote Sensing Images”, Guangzhou Science and Technology Bureau Joint Project, 01/2025 - 12/2026
PI, “Urban Scene Generation and Decision-Making under Multimodal Spatiotemporal Data Fusion”, Guangzhou Education Bureau Talent Project, 01/2025 - 12/2026
PI, “Multi-Source Data Fusion based 3D Geometric Building Modeling”, Open Fund of Key Laboratory of Real Scene Geographical Environment in Anhui Province, 10/2022 - 10/2024
co-PI, “Research on the connectivity of loess micro-landform and its influence on the development of gully system in small watersheds of Chinese Loess Plateau”, National Natural Science Foundation of China General Program, 01/2024 - 12/2027