Liu Liu
- Statistics, Probability and Uncertainty top 0.5%
- Information Systems and Management top 2%
- Statistics and Probability top 2%
- Sociology and Political Science top 10%
- Organic Chemistry
- Co-authors
- J. Michael TarnDavid C. YenQing YangChuan PangJian ZhangXin LaiShi JinSi Zeng
- Topics
- Advanced Statistical Process Monitoring (30 papers)Advanced Statistical Methods and Models (22 papers)Scientific Measurement and Uncertainty Evaluation (18 papers)
- Cited by
- Statistics, Probability and UncertaintyInformation Systems and ManagementStatistics and Probability
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Liu Liu
81 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 163
- Statistics, Probability and Uncertainty 329
- Information Systems and Management 213
- Statistics and Probability 189
- Sociology and Political Science 182
- Organic Chemistry 136
Countries citing papers authored by Liu Liu
This map shows the geographic impact of Liu Liu'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 Liu Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Liu Liu more than expected).
Fields of papers citing papers by Liu Liu
This network shows the impact of papers produced by Liu Liu. 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 Liu Liu. The network helps show where Liu Liu may publish in the future.
Co-authorship network of co-authors of Liu Liu
This figure shows the co-authorship network connecting the top 25 collaborators of Liu Liu. A scholar is included among the top collaborators of Liu Liu 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 Liu Liu. Liu Liu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 0 | |
| 7 | 1 | |
| 8 | 0 | |
| 9 | 18 | |
| 10 | 1 | |
| 11 | 12 | |
| 12 | 13 | |
| 13 | 1 | |
| 14 | 150 | |
| 15 | 6 | |
| 16 | 2 | |
| 17 | 28 | |
| 18 | 15 | |
| 19 | 25 | |
| 20 | Nonexistence of iterative roots of PM functions | 1 |
About Liu Liu
Liu Liu is a scholar working on Statistics, Probability and Uncertainty, Statistics and Probability and Medical Laboratory Technology, having authored 90 papers that have together received 1.4k indexed citations. Recurring topics across this work include Advanced Statistical Process Monitoring (30 papers), Advanced Statistical Methods and Models (22 papers) and Scientific Measurement and Uncertainty Evaluation (18 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (329 citations), Information Systems and Management (213 citations) and Statistics and Probability (189 citations). Liu Liu has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include J. Michael Tarn, David C. Yen, Qing Yang, Chuan Pang, Jian Zhang, Xin Lai, Shi Jin, Si Zeng, Chunhua Chen and Fugee Tsung. Their work appears in journals such as Scientific Reports, Journal of Computational Physics and Neuroscience.
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.