Hancheng Ge
- Computational Mathematics top 0.5%
- Artificial Intelligence top 10%
- Information Systems top 10%
- Computational Mechanics top 10%
- Computer Vision and Pattern Recognition
- Topics
- Tensor decomposition and applications (5 papers)Spam and Phishing Detection (4 papers)Infrastructure Maintenance and Monitoring (4 papers)
- Journals
- Artificial IntelligenceTransportation Research Record Journal of the Transportation Research BoardComputer-Aided Civil and Infrastructure Engineering
- Partner nations
- United StatesSingaporeChina
In The Last Decade
Hancheng Ge
20 papers receiving 388 citations
Peers
Comparison fields: 5 of 70
- Computational Mathematics 153
- Artificial Intelligence 114
- Information Systems 92
- Computational Mechanics 77
- Computer Vision and Pattern Recognition 55
Countries citing papers authored by Hancheng Ge
This map shows the geographic impact of Hancheng Ge'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 Hancheng Ge with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hancheng Ge more than expected).
Fields of papers citing papers by Hancheng Ge
This network shows the impact of papers produced by Hancheng Ge. 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 Hancheng Ge. The network helps show where Hancheng Ge may publish in the future.
Co-authorship network of co-authors of Hancheng Ge
This figure shows the co-authorship network connecting the top 25 collaborators of Hancheng Ge. A scholar is included among the top collaborators of Hancheng Ge 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 Hancheng Ge. Hancheng Ge is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 138 | |
| 3 | 11 | |
| 4 | 45 | |
| 5 | 14 | |
| 6 | 5 | |
| 7 | 1 | |
| 8 | 24 | |
| 9 | 17 | |
| 10 | 28 | |
| 11 | 15 | |
| 12 | Lessons Learned with Prototype Mobile Luminance Measurement System | 3 |
| 13 | 26 | |
| 14 | 1 | |
| 15 | 42 | |
| 16 | 13 | |
| 17 | 9 | |
| 18 | 5 | |
| 19 | Development of Field Performance Evaluation Tools and Program for Pavement Marking Materials: Technical Report | 2 |
| 20 | Intelligent Intersection Traffic Flow Prediction Based on Fuzzy Neural Network | 2 |
About Hancheng Ge
Hancheng Ge is a scholar working on Computational Mathematics, Computer Science Applications and Transportation, having authored 20 papers that have together received 403 indexed citations. Recurring topics across this work include Tensor decomposition and applications (5 papers), Spam and Phishing Detection (4 papers) and Infrastructure Maintenance and Monitoring (4 papers). The work is most often cited by research in Computational Mathematics (153 citations), Computer Science Applications (23 citations) and Information Systems (92 citations). Hancheng Ge has collaborated with scholars based in United States, Singapore and China. Frequent co-authors include James Caverlee, Xia Hu, Qingquan Song, Yunlong Zhang, Kyumin Lee, Steve Webb, Xiao Huang, Cheng Cao, Yunlong Zhang and Anna Squicciarini. Their work appears in journals such as Artificial Intelligence, Transportation Research Record Journal of the Transportation Research Board and Computer-Aided Civil and Infrastructure Engineering.
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.