Sheng Wu

1.6k total citations · 1 hit paper
38 papers, 1.2k citations indexed

About

Sheng Wu is a scholar working on Transportation, Sociology and Political Science and Artificial Intelligence. According to data from OpenAlex, Sheng Wu has authored 38 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Transportation, 9 papers in Sociology and Political Science and 9 papers in Artificial Intelligence. Recurrent topics in Sheng Wu's work include Human Mobility and Location-Based Analysis (9 papers), Traffic Prediction and Management Techniques (8 papers) and Transportation Planning and Optimization (8 papers). Sheng Wu is often cited by papers focused on Human Mobility and Location-Based Analysis (9 papers), Traffic Prediction and Management Techniques (8 papers) and Transportation Planning and Optimization (8 papers). Sheng Wu collaborates with scholars based in China, Taiwan and United States. Sheng Wu's co-authors include Cathy S. Lin, Ray J. Tsai, Feng Lu, Shifen Cheng, Peng Peng, Tung‐Ching Lin, Zhixiang Fang, Hengcai Zhang, Xiping Yang and Peixiao Wang and has published in prestigious journals such as Scientific Reports, Expert Systems with Applications and IEEE Access.

In The Last Decade

Sheng Wu

32 papers receiving 1.1k citations

Hit Papers

Integrating perceived playfulness into expectation-confir... 2004 2026 2011 2018 2004 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sheng Wu China 13 627 554 282 207 189 38 1.2k
Reza Barkhi United States 17 243 0.4× 260 0.5× 249 0.9× 125 0.6× 32 0.2× 56 1.1k
Rubina Islam United Kingdom 6 210 0.3× 385 0.7× 74 0.3× 54 0.3× 62 0.3× 8 784
Hong Sheng United States 16 418 0.7× 387 0.7× 115 0.4× 98 0.5× 46 0.2× 37 1.3k
Hueiju Yu Taiwan 10 360 0.6× 557 1.0× 209 0.7× 97 0.5× 37 0.2× 11 944
Valerie Trifts Canada 8 486 0.8× 675 1.2× 223 0.8× 34 0.2× 51 0.3× 14 1.4k
Dothang Truong United States 20 236 0.4× 177 0.3× 125 0.4× 21 0.1× 93 0.5× 63 1.1k
Guoyin Jiang China 18 209 0.3× 423 0.8× 92 0.3× 116 0.6× 51 0.3× 48 906
Louis Sanzogni Australia 19 329 0.5× 420 0.8× 206 0.7× 38 0.2× 28 0.1× 54 1.2k
Di Xu China 11 150 0.2× 360 0.6× 73 0.3× 51 0.2× 50 0.3× 31 704
Pirkko Walden Finland 15 502 0.8× 487 0.9× 162 0.6× 46 0.2× 23 0.1× 67 1.0k

Countries citing papers authored by Sheng Wu

Since Specialization
Citations

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

Fields of papers citing papers by Sheng Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sheng Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Sheng Wu. A scholar is included among the top collaborators of Sheng Wu 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 Sheng Wu. Sheng Wu 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.
Deng, Min, et al.. (2025). Predicting crowd flows via compressed sensing with spatial heterogeneity: an efficient GeoAI framework. International Journal of Geographical Information Systems. 40(4). 947–978.
2.
Wu, Sheng, et al.. (2025). Predicting tourism demand using data based on a two-stage feature selection: A hybrid deep learning approach incorporating Time2Vec. Engineering Applications of Artificial Intelligence. 163. 112768–112768.
3.
Wu, Sheng, et al.. (2025). VoxT-GNN: A 3D object detection approach from point cloud based on voxel-level transformer and graph neural network. Information Processing & Management. 62(4). 104155–104155. 5 indexed citations
4.
Wang, Peixiao, et al.. (2025). Predicting the Next Location of Urban Individuals via a Representation-Enhanced Multi-View Learning Network. ISPRS International Journal of Geo-Information. 14(8). 302–302.
5.
Xu, Weiming, Shiyu Yang, Juan Wang, et al.. (2024). A Hierarchical Graph-Enhanced Transformer Network for Remote Sensing Scene Classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 17. 20315–20330. 4 indexed citations
6.
Wang, Peixiao, Hengcai Zhang, Shifen Cheng, et al.. (2023). A lightweight spatiotemporal graph dilated convolutional network for urban sensor state prediction. Sustainable Cities and Society. 101. 105105–105105. 7 indexed citations
7.
Wu, Sheng, et al.. (2023). Named Entity Recognition of Chinese Crop Diseases and Pests Based on RoBERTa-wwm with Adversarial Training. Agronomy. 13(3). 941–941. 12 indexed citations
8.
Zhang, Yu, et al.. (2023). An urban crowd flow model integrating geographic characteristics. Scientific Reports. 13(1). 1695–1695. 6 indexed citations
9.
Wu, Sheng. (2023). Factors affecting rumor spreading of social network sites. Journal of Statistics and Management Systems. 26(4). 801–821. 1 indexed citations
10.
Zhao, Zhiyuan, et al.. (2022). Interday Stability of Taxi Travel Flow in Urban Areas. ISPRS International Journal of Geo-Information. 11(12). 590–590. 6 indexed citations
11.
Wu, Sheng, et al.. (2022). Spatial characteristics and influential mechanism of the coupling coordination degree of urban accessibility and human development index in China. Environmental Science and Pollution Research. 29(20). 29793–29807. 13 indexed citations
12.
Chang, Christina Ling-hsing & Sheng Wu. (2022). The Circumplex Model for Structuring Career Anchors of the IT/IS Personnel. Journal of Global Information Management. 30(1). 1–27. 1 indexed citations
13.
Zhao, Zhiyuan, Shih‐Lung Shaw, Ling Yin, et al.. (2019). The effect of temporal sampling intervals on typical human mobility indicators obtained from mobile phone location data. International Journal of Geographical Information Systems. 33(7). 1471–1495. 34 indexed citations
14.
Wang, Peixiao, et al.. (2019). A Hybrid Markov and LSTM Model for Indoor Location Prediction. IEEE Access. 7. 185928–185940. 15 indexed citations
15.
Cheng, Shifen, Feng Lu, Peng Peng, & Sheng Wu. (2018). A Spatiotemporal Multi-View-Based Learning Method for Short-Term Traffic Forecasting. ISPRS International Journal of Geo-Information. 7(6). 218–218. 21 indexed citations
16.
Hsu, Po‐Hsuan, et al.. (2016). Asset Allocation Strategies, the 1/N Rule, and Data Snooping. SSRN Electronic Journal.
17.
Lin, Cathy S. & Sheng Wu. (2015). Exploring antecedents of online group-buying: Social commerce perspective. Human Systems Management. 34(2). 133–147. 23 indexed citations
18.
Lin, Tung‐Ching, et al.. (2011). Exploring the affect factors of knowledge sharing behavior: The relations model theory perspective. Expert Systems with Applications. 39(1). 751–764. 75 indexed citations
19.
Wu, Sheng. (2010). Research on place names and address segmentation in geocoding system. Cehui kexue. 1 indexed citations
20.
Wu, Sheng. (2008). DESIGN AND REALIZATION OF ADDRESS MATCHING ENGINE IN GEOCODING SYSTEM.

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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