Weiming Huang

1.4k total citations · 1 hit paper
65 papers, 862 citations indexed

About

Weiming Huang is a scholar working on Geography, Planning and Development, Transportation and Artificial Intelligence. According to data from OpenAlex, Weiming Huang has authored 65 papers receiving a total of 862 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Geography, Planning and Development, 14 papers in Transportation and 13 papers in Artificial Intelligence. Recurrent topics in Weiming Huang's work include Geographic Information Systems Studies (15 papers), Human Mobility and Location-Based Analysis (13 papers) and Data Management and Algorithms (12 papers). Weiming Huang is often cited by papers focused on Geographic Information Systems Studies (15 papers), Human Mobility and Location-Based Analysis (13 papers) and Data Management and Algorithms (12 papers). Weiming Huang collaborates with scholars based in China, Singapore and Sweden. Weiming Huang's co-authors include Haigang Sui, Wenqing Feng, Chuan Xu, Lizhen Cui, Lars Harrie, Daokun Zhang, Meng Chen, Gao Cong, Yao Yao and Gengchen Mai and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and IEEE Access.

In The Last Decade

Weiming Huang

61 papers receiving 823 citations

Hit Papers

On the Opportunities and Challenges of Foundation Models ... 2024 2026 2025 2024 10 20 30 40

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Weiming Huang China 17 217 179 156 150 141 65 862
Xiongfeng Yan China 13 152 0.7× 90 0.5× 87 0.6× 154 1.0× 216 1.5× 37 661
Di Zhu China 18 369 1.7× 79 0.4× 607 3.9× 170 1.1× 88 0.6× 50 1.2k
Haihong Zhu China 20 163 0.8× 100 0.6× 66 0.4× 226 1.5× 83 0.6× 79 1.3k
Jochen Schiewe Germany 13 112 0.5× 98 0.5× 29 0.2× 220 1.5× 169 1.2× 59 646
Dongyang Hou China 17 208 1.0× 224 1.3× 33 0.2× 133 0.9× 69 0.5× 54 621
Emily Schnebele United States 7 213 1.0× 61 0.3× 62 0.4× 37 0.2× 109 0.8× 8 569
Mingqiang Guo China 13 80 0.4× 174 1.0× 43 0.3× 179 1.2× 41 0.3× 48 507
Xicheng Tan China 17 157 0.7× 129 0.7× 28 0.2× 80 0.5× 53 0.4× 52 687
Yakun Xie China 18 123 0.6× 258 1.4× 27 0.2× 306 2.0× 73 0.5× 48 863
Sylvain Lobry France 13 84 0.4× 162 0.9× 50 0.3× 378 2.5× 60 0.4× 31 734

Countries citing papers authored by Weiming Huang

Since Specialization
Citations

This map shows the geographic impact of Weiming Huang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Weiming Huang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Weiming Huang more than expected).

Fields of papers citing papers by Weiming Huang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Weiming Huang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Weiming Huang. The network helps show where Weiming Huang may publish in the future.

Co-authorship network of co-authors of Weiming Huang

This figure shows the co-authorship network connecting the top 25 collaborators of Weiming Huang. A scholar is included among the top collaborators of Weiming Huang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Weiming Huang. Weiming Huang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Huang, Weiming, et al.. (2025). A diffusion-stimulated CT-US registration model with self-supervised learning and synthetic-to-real domain adaptation. Computerized Medical Imaging and Graphics. 123. 102562–102562. 1 indexed citations
2.
Janowicz, Krzysztof, Gengchen Mai, Weiming Huang, et al.. (2025). GeoFM: how will geo-foundation models reshape spatial data science and GeoAI?. International Journal of Geographical Information Systems. 39(9). 1849–1865. 2 indexed citations
3.
Cao, Jinzhou, Weiming Huang, Dongsheng Chen, et al.. (2025). UrbanMMCL: Urban region representations via multi-modal and multi-graph self-supervised contrastive learning. ISPRS Journal of Photogrammetry and Remote Sensing. 232. 75–93.
4.
Ai, Tinghua, Shishuo Xu, Yan Zhang, et al.. (2025). Learning dual context aware POI representations for geographic mapping. International Journal of Applied Earth Observation and Geoinformation. 142. 104683–104683.
5.
Liu, Wei, et al.. (2025). Fairness identification of large language models in recommendation. Scientific Reports. 15(1). 5516–5516.
6.
Huang, Weiming, et al.. (2025). Self-supervised representation learning for geospatial objects: A survey. Information Fusion. 123. 103265–103265. 5 indexed citations
7.
Tao, Ming, et al.. (2024). Optimized-CNN enabled Facial Emotion Recognition within Collaborative Edge Computing. 12–17. 3 indexed citations
8.
Huang, Weiming, et al.. (2024). Urban Region Embedding via Multi-View Contrastive Prediction. Proceedings of the AAAI Conference on Artificial Intelligence. 38(8). 8724–8732. 8 indexed citations
9.
Mai, Gengchen, Weiming Huang, Suhang Song, et al.. (2024). On the Opportunities and Challenges of Foundation Models for GeoAI (Vision Paper). ACM Transactions on Spatial Algorithms and Systems. 10(2). 1–46. 45 indexed citations breakdown →
10.
Liu, Pengyuan, et al.. (2024). Sensing climate justice: A multi-hyper graph approach for classifying urban heat and flood vulnerability through street view imagery. Sustainable Cities and Society. 118. 106016–106016. 3 indexed citations
12.
Yu, Huafei, Tinghua Ai, Min Yang, Weiming Huang, & Lars Harrie. (2023). A graph autoencoder network to measure the geometric similarity of drainage networks in scaling transformation. International Journal of Digital Earth. 16(1). 1828–1852. 10 indexed citations
13.
Huang, Weiming, Xiuyuan Zhang, Shihong Du, et al.. (2023). Geographic mapping with unsupervised multi-modal representation learning from VHR images and POIs. ISPRS Journal of Photogrammetry and Remote Sensing. 201. 193–208. 34 indexed citations
14.
Zhang, Dabin, et al.. (2023). Towards an Integrated View of Semantic Annotation for POIs with Spatial and Textual Information. 2441–2449. 4 indexed citations
15.
Yao, Yao, et al.. (2023). Unsupervised land-use change detection using multi-temporal POI embedding. International Journal of Geographical Information Systems. 37(11). 2392–2415. 13 indexed citations
16.
Yu, Fuqiang, Lizhen Cui, Huanhuan Chen, et al.. (2022). HealthNet: A Health Progression Network via Heterogeneous Medical Information Fusion. IEEE Transactions on Neural Networks and Learning Systems. 34(10). 6940–6954. 5 indexed citations
17.
Huang, Weiming, et al.. (2019). Assessment and Benchmarking of Spatially Enabled RDF Stores for the Next Generation of Spatial Data Infrastructure. ISPRS International Journal of Geo-Information. 8(7). 310–310. 17 indexed citations
18.
Huang, Weiming, et al.. (2019). Privacy Protection for Recommendation System: A Survey. Journal of Physics Conference Series. 1325(1). 12087–12087. 14 indexed citations
19.
Feng, Wenqing, Haigang Sui, Jihui Tu, Kaimin Sun, & Weiming Huang. (2017). Change Detection Method for High Resolution Remote Sensing Images Using Random Forest. SHILAP Revista de lepidopterología. 5 indexed citations
20.
Chen, Chin‐Wen, et al.. (2009). P‐83: An Improvement of Color Difference between Two Eyes of Stereoscopic Display with Glasses. SID Symposium Digest of Technical Papers. 40(1). 1431–1433. 4 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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