Senzhang Wang

6.7k citations
157 papers · 4.1k indexed · 4 hit papers · h-index 35

Senzhang Wang

146 papers receiving 4.0k citations

Hit Papers

Dynamic graph convolutional network for long-term traffic...1642019202620212023100200300400

Peers

Senzhang Wang
Comparison fields: 5 of 127
  • Transportation 980
  • Building and Construction 1.2k
  • Artificial Intelligence 1.8k
  • Statistical and Nonlinear Physics 548
  • Signal Processing 453
Replace Jing Jiang with:
Jing Jiang Australia
Hao Peng China
Yanjie Fu United States
Depeng Jin China
Guojie Song China
Kai Zheng China
Leilei Sun China
Leye Wang China
Goce Trajcevski United States
Yanchi Liu United States
Senzhang Wang relative to Jing Jiang Australia Jing Jiang's profile →
Citations per field
00.5×1.6×
Jing Jiang · 1×
Citations per year

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

The 25 scholars most cited alongside Senzhang Wang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Senzhang Wang Line = papers co-authored together Senzhang Wang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 202514
3 20251
4 20251
5 20250
6 202420
7 20241
8 20246
9 202422
10 202417
11 20237
12 202321
13 202310
14 202230
15 202110
16
Spatial temporal incidence dynamic graph neural networks for traffic flow forecastingbreakdown →
2020243
17
Decode with Template: Content Preserving Sentiment Transfer
20203
18 2019124
19
Deep Irregular Convolutional Residual LSTM for Urban Traffic Passenger Flows Predictionbreakdown →
2019225
20
Negative influence minimizing by blocking nodes in social networks
201323

About Senzhang Wang

Senzhang Wang is a scholar working on Transportation, Building and Construction and Statistical and Nonlinear Physics, having authored 157 papers that have together received 4.1k indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (42 papers), Traffic Prediction and Management Techniques (35 papers), Complex Network Analysis Techniques (32 papers), Recommender Systems and Techniques (30 papers), Human Mobility and Location-Based Analysis (24 papers), Topic Modeling (20 papers), Time Series Analysis and Forecasting (13 papers) and Advanced Text Analysis Techniques (11 papers). The work is most often cited by research in Transportation (980 citations), Building and Construction (1.2k citations) and Artificial Intelligence (1.8k citations). Senzhang Wang has collaborated with scholars based in China, United States and Hong Kong. Frequent 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. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, Knowledge and Information Systems, Knowledge-Based Systems, IEEE Transactions on Intelligent Transportation Systems and World Wide Web.

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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