Dr. Tengping Jiang | Nanjing Normal University | China
Dr. Tengping Jiang is an accomplished researcher and Associate Professor at the School of Geography, Nanjing Normal University, where he also serves as Deputy Director of the Department of Surveying and Mapping Engineering. His research focuses on 3D reconstruction, scene understanding, point cloud processing, and deep learning-based computer vision, with applications spanning intelligent transportation systems, digital twin cities, and plant phenotyping. Dr. Jiang earned his Ph.D. from the State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University, under the supervision of Prof. Bisheng Yang, and later conducted visiting research at the Eastern Institute of Technology, Ningbo, guided by Prof. Wenjun Zeng (IEEE Fellow). His scholarly contributions have advanced the integration of artificial intelligence with geospatial technologies, particularly through the development of innovative neural network architectures for semantic segmentation and structural feature extraction from LiDAR and urban scene point clouds. His highly cited works, published in leading journals such as ISPRS Journal of Photogrammetry and Remote Sensing and IEEE Transactions on Geoscience and Remote Sensing, include groundbreaking studies like RailSeg, LWSNet, and ShrimpSeg, which address complex challenges in automated urban and environmental data interpretation. Dr. Jiang has received multiple prestigious research grants, including the NSFC Young Scientists Fund (2025–2027) and the Natural Science Foundation of Jiangsu Province Young Scientists Fund (2024–2027). His projects emphasize fine-grained scene extraction, LiDAR data fusion, and energy-efficient modeling of urban environments. Beyond research, Dr. Jiang contributes extensively to academic service, serving on the Youth Editorial Boards of Plant Phenotype, Agriculture Communications, and Climate Smart Agriculture, and as a reviewer for top-tier conferences like CVPR and NeurIPS. Through his interdisciplinary expertise, Dr. Jiang continues to push the boundaries of 3D geospatial intelligence and its transformative applications in smart and sustainable cities.
Profiles: Orcid
Featured Publications
Jiang, T., Wang, Y., Liu, S., Zhang, Q., Zhao, L., & Sun, J. (2023). Instance recognition of street trees from urban point clouds using a three-stage neural network. ISPRS Journal of Photogrammetry and Remote Sensing, 109, 305–334. https://doi.org/10.1016/j.isprsjprs.2023.04.010
Jiang, T., Zhang, Q., Liu, S., Liang, C., Dai, L., Zhang, Z., Sun, J., & Wang, Y. (2023). LWSNet: A point-based segmentation network for leaf–wood separation of individual trees. Forests, 14(7), 1303. https://doi.org/10.3390/f14071303
Jiang, T., Liu, S., Zhang, Q., Xu, X., Sun, J., & Wang, Y. (2023, September). Segmentation of individual trees in urban MLS point clouds using a deep learning framework based on cylindrical convolution network. International Journal of Applied Earth Observation and Geoinformation, 123, 103473. https://doi.org/10.1016/j.jag.2023.103473
Jiang, T., Yang, B., Wang, Y., Dai, L., Qiu, B., Liu, S., Li, S., Zhang, Q., Jin, X., & Zeng, W. (2023). RailSeg: Learning local–global feature aggregation with contextual information for railway point cloud semantic segmentation. IEEE Transactions on Geoscience and Remote Sensing, 61, 5704929. https://doi.org/10.1109/TGRS.2023.3319950
Jiang, T., Wang, Y., Zhang, Z., Liu, S., Dai, L., Yang, Y., Jin, X., & Zeng, W. (2023). Extracting 3-D structural lines of buildings from ALS point clouds using graph neural network embedded with corner information. IEEE Transactions on Geoscience and Remote Sensing, 61, 5702615. https://doi.org/10.1109/TGRS.2023.3278589