| (he/him) |
| University of Leeds |
| Current Position | Lecturer in Urban Data Science |
| W.Huang@leeds.ac.uk | |
| Department(s) | School of Geography |
| ECR | Yes |
| YES.DTN Core Themes | Dynamic Earth, Natural Hazards & Earth Processes |
| Profile(s) | Weiming Huang (0000-0002-3208-4208) – ORCID |
Key Research Interests
- Remote sensing
- Machine learning
- Information integration
- Environmental data science
- Urban analytics
Recent Key Papers
- Mai, G., Huang, W., Sun, J., Song, S., Mishra, D., Liu, N., … & Lao, N. (2024). On the opportunities and challenges of foundation models for geoai (vision paper). ACM Transactions on Spatial Algorithms and Systems, 10(2), 1-46. https://doi.org/10.1145/3653070
- Balsebre, P., Huang, W., Cong, G., & Li, Y. (2024, October). City foundation models for learning general purpose representations from OpenStreetMap. In Proceedings of the 33rd ACM International Conference on Information and Knowledge Management (pp. 87-97). https://doi.org/10.1145/3627673.3679662
- Yan, S., Yao, X., Sun, J., Huang, W., Yang, L., Zhang, C., … & Zhu, D. (2024). TSANet: A deep learning framework for the delineation of agricultural fields utilizing satellite image time series. Computers and Electronics in Agriculture, 220, 108902. https://doi.org/10.1016/j.compag.2024.108902