Qiushi Cao
- Industrial and Manufacturing Engineering top 5%
- Artificial Intelligence
- Control and Systems Engineering top 10%
- Medical Laboratory Technology top 5%
- Safety, Risk, Reliability and Quality top 10%
- Co-authors
- Christoph ReichCécilia Zanni-MerkFrançois de Bertrand de BeuvronAhmed SametArnold BeckmannCinzia GiannettiFei QiaoYuan Sui
- Topics
- Digital Transformation in Industry (6 papers)Flexible and Reconfigurable Manufacturing Systems (3 papers)Semantic Web and Ontologies (3 papers)
In The Last Decade
Qiushi Cao
17 papers receiving 275 citations
Peers
Comparison fields: 5 of 53
- Industrial and Manufacturing Engineering 146
- Artificial Intelligence 77
- Control and Systems Engineering 66
- Medical Laboratory Technology 40
- Safety, Risk, Reliability and Quality 30
Countries citing papers authored by Qiushi Cao
This map shows the geographic impact of Qiushi Cao'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 Qiushi Cao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qiushi Cao more than expected).
Fields of papers citing papers by Qiushi Cao
This network shows the impact of papers produced by Qiushi Cao. 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 Qiushi Cao. The network helps show where Qiushi Cao may publish in the future.
Co-authorship network of co-authors of Qiushi Cao
This figure shows the co-authorship network connecting the top 25 collaborators of Qiushi Cao. A scholar is included among the top collaborators of Qiushi Cao 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 Qiushi Cao. Qiushi Cao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 15 | |
| 2 | 1 | |
| 3 | 2 | |
| 4 | 3 | |
| 5 | 1 | |
| 6 | 17 | |
| 7 | 20 | |
| 8 | 5 | |
| 9 | 82 | |
| 10 | 13 | |
| 11 | 2 | |
| 12 | 24 | |
| 13 | 5 | |
| 14 | 57 | |
| 15 | 35 | |
| 16 | Semantic Technologies for the Modeling of Condition Monitoring Knowledge in the Framework of Industry 4.0. | 3 |
| 17 | 11 |
About Qiushi Cao
Qiushi Cao is a scholar working on Medical Laboratory Technology, Industrial and Manufacturing Engineering and Management Science and Operations Research, having authored 17 papers that have together received 296 indexed citations. Recurring topics across this work include Digital Transformation in Industry (6 papers), Flexible and Reconfigurable Manufacturing Systems (3 papers) and Semantic Web and Ontologies (3 papers). The work is most often cited by research in Medical Laboratory Technology (40 citations), Industrial and Manufacturing Engineering (146 citations) and Safety, Risk, Reliability and Quality (30 citations). Qiushi Cao has collaborated with scholars based in France, Germany and China. Frequent co-authors include Christoph Reich, Cécilia Zanni-Merk, François de Bertrand de Beuvron, Ahmed Samet, Arnold Beckmann, Cinzia Giannetti, Fei Qiao, Yuan Sui, Wei Yan and Wanjing Wang. Their work appears in journals such as Marine Drugs, Engineering Applications of Artificial Intelligence and Computers in Industry.
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.