Senzhang Wang

6.7k total citations · 4 hit papers
157 papers, 4.1k citations indexed

About

Senzhang Wang is a scholar working on Artificial Intelligence, Information Systems and Building and Construction. According to data from OpenAlex, Senzhang Wang has authored 157 papers receiving a total of 4.1k indexed citations (citations by other indexed papers that have themselves been cited), including 83 papers in Artificial Intelligence, 40 papers in Information Systems and 37 papers in Building and Construction. Recurrent topics in Senzhang Wang's work include Advanced Graph Neural Networks (42 papers), Traffic Prediction and Management Techniques (35 papers) and Complex Network Analysis Techniques (32 papers). Senzhang Wang is often cited by papers focused on Advanced Graph Neural Networks (42 papers), Traffic Prediction and Management Techniques (35 papers) and Complex Network Analysis Techniques (32 papers). Senzhang Wang collaborates with scholars based in China, United States and Hong Kong. Senzhang Wang's co-authors include Philip S. Yu, Jiannong Cao, Zhoujun Li, Hao Peng, Zhiqiu Huang, Lifang He, Bowen Du, Hao Miao, Lihong Wang and Xiaoming Zhang and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Pattern Analysis and Machine Intelligence and Expert Systems with Applications.

In The Last Decade

Senzhang Wang

146 papers receiving 4.0k citations

Hit Papers

Deep Learning for Spatio-Temporal Data Mining: A Survey 2019 2026 2021 2023 2020 2020 2019 2021 100 200 300 400
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Deep Learning for Spatio-Temporal Data Mining: A Survey
    2020 460 citations Senzhang Wang, Jiannong Cao et al. IEEE Transactions on Knowledge and Data Engineering profile →
  2. Spatial temporal incidence dynamic graph neural networks for traffic flow forecasting
    2020 243 citations Hao Peng, Bowen Du et al. Information Sciences profile →
  3. Deep Irregular Convolutional Residual LSTM for Urban Traffic Passenger Flows Prediction
    2019 225 citations Bowen Du, Hao Peng et al. IEEE Transactions on Intelligent Transportation Systems profile →
  4. Dynamic graph convolutional network for long-term traffic flow prediction with reinforcement learning
    2021 164 citations Hao Peng, Bowen Du et al. Information Sciences profile →

Peers

Senzhang Wang
Jing Jiang Australia
Guojie Song China
Hao Peng China
Yanjie Fu United States
Kai Zheng China
Yanchi Liu United States
Goce Trajcevski United States
Leilei Sun China
Leye Wang China
Depeng Jin China
Jing Jiang Australia
Senzhang Wang
Citations per year, relative to Senzhang Wang Senzhang Wang (= 1×) peers Jing Jiang

Countries citing papers authored by Senzhang Wang

Since Specialization
Citations

This map shows the geographic impact of Senzhang Wang'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 Senzhang Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Senzhang Wang more than expected).

Fields of papers citing papers by Senzhang Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Senzhang Wang. 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 Senzhang Wang. The network helps show where Senzhang Wang may publish in the future.

Co-authorship network of co-authors of Senzhang Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Senzhang Wang. A scholar is included among the top collaborators of Senzhang Wang 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 Senzhang Wang. Senzhang Wang 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.
Chen, Jinpeng, Huan Li, Senzhang Wang, et al.. (2025). Leveraging Multimodal Data and Side Users for Diffusion Cross-Domain Recommendation. 6451–6460.
2.
Huang, Feiran, et al.. (2025). Large Language Model Simulator for Cold-Start Recommendation. 261–270. 14 indexed citations
3.
4.
Ju, Wei, Yifan Wang, Zhiping Xiao, et al.. (2025). A Survey of Graph Neural Networks in Real World: Imbalance, Noise, Privacy and OOD Challenges. IEEE Transactions on Pattern Analysis and Machine Intelligence. 48(3). 3036–3055. 1 indexed citations
5.
Yang, Z., Jinpeng Chen, Huan Li, et al.. (2025). STEP: Stepwise Curriculum Learning for Context-Knowledge Fusion in Conversational Recommendation. ArXiv.org. 3824–3833.
6.
Zhang, Peiyan, Xi Zhang, Chaozhuo Li, et al.. (2024). TransGNN: Harnessing the Collaborative Power of Transformers and Graph Neural Networks for Recommender Systems. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 1285–1295. 20 indexed citations
7.
Yuan, Guan, et al.. (2024). An Efficient Multi-View Heterogeneous Hypergraph Convolutional Network for Heterogeneous Information Network Representation Learning. IEEE Transactions on Big Data. 11(3). 1144–1157. 1 indexed citations
8.
Yuan, Zheng, et al.. (2024). Multi-Behavior Collaborative Filtering with Partial Order Graph Convolutional Networks. 6257–6268. 6 indexed citations
9.
Xu, Yue, Sheng Zhou, Wenbing Huang, et al.. (2024). Macro Graph Neural Networks for Online Billion-Scale Recommender Systems. PolyU Institutional Research Archive (Hong Kong Polytechnic University). 3598–3608. 22 indexed citations
10.
11.
Song, Xiao, et al.. (2023). HN-GCCF: High-order neighbor-enhanced graph convolutional collaborative filtering. Knowledge-Based Systems. 283. 111122–111122. 7 indexed citations
12.
Li, Chaozhuo, et al.. (2023). Beyond the Overlapping Users: Cross-Domain Recommendation via Adaptive Anchor Link Learning. 1488–1497. 21 indexed citations
13.
Li, Jianxin, Hao Peng, Senzhang Wang, et al.. (2023). A Robust and Generalized Framework for Adversarial Graph Embedding. IEEE Transactions on Knowledge and Data Engineering. 35(11). 11004–11018. 10 indexed citations
14.
Zhao, Xusheng, Qiong Dai, Jia Wu, et al.. (2022). Multi-View Tensor Graph Neural Networks Through Reinforced Aggregation. IEEE Transactions on Knowledge and Data Engineering. 35(4). 4077–4091. 30 indexed citations
15.
Li, He, Jianbin Huang, Jiangtao Cui, et al.. (2021). Group Reassignment for Dynamic Edge Partitioning. IEEE Transactions on Parallel and Distributed Systems. 32(10). 2477–2490. 10 indexed citations
16.
Peng, Hao, Bowen Du, Md Zakirul Alam Bhuiyan, et al.. (2020). Spatial temporal incidence dynamic graph neural networks for traffic flow forecasting. Information Sciences. 521. 277–290. 243 indexed citations breakdown →
17.
Wen, Zhiyuan, Jiannong Cao, Ruosong Yang, & Senzhang Wang. (2020). Decode with Template: Content Preserving Sentiment Transfer. Language Resources and Evaluation. 4671–4679. 3 indexed citations
18.
Peng, Hao, Jianxin Li, Senzhang Wang, et al.. (2019). Hierarchical Taxonomy-Aware and Attentional Graph Capsule RCNNs for Large-Scale Multi-Label Text Classification. IEEE Transactions on Knowledge and Data Engineering. 33(6). 2505–2519. 124 indexed citations
19.
Du, Bowen, Hao Peng, Senzhang Wang, et al.. (2019). Deep Irregular Convolutional Residual LSTM for Urban Traffic Passenger Flows Prediction. IEEE Transactions on Intelligent Transportation Systems. 21(3). 972–985. 225 indexed citations breakdown →
20.
Wang, Senzhang, et al.. (2013). Negative influence minimizing by blocking nodes in social networks. National Conference on Artificial Intelligence. 134–136. 23 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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