Peng Cheng
- Computer Science Applications top 0.5%
- Transportation top 2%
- Artificial Intelligence top 5%
- Automotive Engineering top 5%
- Management Science and Operations Research top 2%
- Topics
- Mobile Crowdsensing and Crowdsourcing (17 papers)Privacy-Preserving Technologies in Data (12 papers)Transportation and Mobility Innovations (9 papers)
In The Last Decade
Peng Cheng
54 papers receiving 989 citations
Peers
Comparison fields: 5 of 79
- Computer Science Applications 586
- Transportation 297
- Artificial Intelligence 247
- Automotive Engineering 227
- Management Science and Operations Research 219
Countries citing papers authored by Peng Cheng
This map shows the geographic impact of Peng Cheng'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 Peng Cheng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peng Cheng more than expected).
Fields of papers citing papers by Peng Cheng
This network shows the impact of papers produced by Peng Cheng. 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 Peng Cheng. The network helps show where Peng Cheng may publish in the future.
Co-authorship network of co-authors of Peng Cheng
This figure shows the co-authorship network connecting the top 25 collaborators of Peng Cheng. A scholar is included among the top collaborators of Peng Cheng 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 Peng Cheng. Peng Cheng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 12 | |
| 5 | 0 | |
| 6 | 3 | |
| 7 | 0 | |
| 8 | 1 | |
| 9 | 12 | |
| 10 | 5 | |
| 11 | 3 | |
| 12 | 2 | |
| 13 | 8 | |
| 14 | 12 | |
| 15 | 40 | |
| 16 | Research on mechanisms of the influential factors of spatial knowledge spill-off | 2 |
| 17 | Properties on the Average Number of Spanning Trees in Connected Spanning Subgraphs for an Undirected Graph | 1 |
| 18 | Complexity of Computing the Expected Maximum Number of Edge-Disjoint s-t Paths on Probabilistic Graphs. | 0 |
| 19 | Computing the Expected Maximum Number of Vertex-Disjoint s-t Paths in a Probabilistic Basically Series-Parallel Digraph | 1 |
| 20 | AN INEQUALITY OF MOMENTS | 1 |
About Peng Cheng
Peng Cheng is a scholar working on Computer Science Applications, Transportation and Signal Processing, having authored 66 papers that have together received 999 indexed citations. Recurring topics across this work include Mobile Crowdsensing and Crowdsourcing (17 papers), Privacy-Preserving Technologies in Data (12 papers) and Transportation and Mobility Innovations (9 papers). The work is most often cited by research in Computer Science Applications (586 citations), Transportation (297 citations) and Automotive Engineering (227 citations). Peng Cheng has collaborated with scholars based in China, Hong Kong and Australia. Frequent co-authors include Lei Chen, Xiang Lian, Zhao Chen, Jizhong Zhao, Jinsong Han, Xuemin Lin, Libin Zheng, Rui Fu, Jieping Ye and Lei Chen. Their work appears in journals such as The Science of The Total Environment, International Journal of Radiation Oncology*Biology*Physics and The Journal of Organic Chemistry.
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.