Ridwan A. Sanusi
- Statistics, Probability and Uncertainty top 0.5%
- Statistics and Probability top 2%
- Control and Systems Engineering top 10%
- Medical Laboratory Technology top 5%
- Management Science and Operations Research
- Co-authors
- Muhammad RiazNurudeen A. AdegokeNasir AbbasMin XieMatthew D. M. PawleyAdam N. H. SmithAmitava MukherjeeMu’azu Ramat Abujiya
- Topics
- Advanced Statistical Process Monitoring (14 papers)Advanced Statistical Methods and Models (9 papers)Scientific Measurement and Uncertainty Evaluation (8 papers)
- Cited by
- Statistics, Probability and UncertaintyStatistics and ProbabilityMedical Laboratory Technology
- Partner nations
- Hong KongSaudi ArabiaCanada
In The Last Decade
Ridwan A. Sanusi
22 papers receiving 415 citations
Peers
Comparison fields: 5 of 63
- Statistics, Probability and Uncertainty 380
- Statistics and Probability 245
- Control and Systems Engineering 102
- Medical Laboratory Technology 34
- Management Science and Operations Research 32
Countries citing papers authored by Ridwan A. Sanusi
This map shows the geographic impact of Ridwan A. Sanusi'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 Ridwan A. Sanusi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ridwan A. Sanusi more than expected).
Fields of papers citing papers by Ridwan A. Sanusi
This network shows the impact of papers produced by Ridwan A. Sanusi. 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 Ridwan A. Sanusi. The network helps show where Ridwan A. Sanusi may publish in the future.
Co-authorship network of co-authors of Ridwan A. Sanusi
This figure shows the co-authorship network connecting the top 25 collaborators of Ridwan A. Sanusi. A scholar is included among the top collaborators of Ridwan A. Sanusi 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 Ridwan A. Sanusi. Ridwan A. Sanusi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 1 | |
| 3 | 7 | |
| 4 | 3 | |
| 5 | 8 | |
| 6 | 1 | |
| 7 | 48 | |
| 8 | 11 | |
| 9 | 5 | |
| 10 | 23 | |
| 11 | 47 | |
| 12 | 19 | |
| 13 | 47 | |
| 14 | 41 | |
| 15 | 56 | |
| 16 | 45 | |
| 17 | 6 | |
| 18 | 12 | |
| 19 | A Class of Regression Estimator with Cum-Dual Ratio Estimator as Intercept | 7 |
| 20 | 3 |
About Ridwan A. Sanusi
Ridwan A. Sanusi is a scholar working on Statistics, Probability and Uncertainty, Statistics and Probability and Medical Laboratory Technology, having authored 22 papers that have together received 428 indexed citations. Recurring topics across this work include Advanced Statistical Process Monitoring (14 papers), Advanced Statistical Methods and Models (9 papers) and Scientific Measurement and Uncertainty Evaluation (8 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (380 citations), Statistics and Probability (245 citations) and Medical Laboratory Technology (34 citations). Ridwan A. Sanusi has collaborated with scholars based in Hong Kong, Saudi Arabia and Canada. Frequent co-authors include Muhammad Riaz, Nurudeen A. Adegoke, Nasir Abbas, Min Xie, Matthew D. M. Pawley, Adam N. H. Smith, Amitava Mukherjee, Mu’azu Ramat Abujiya, Sin Yin Teh and Michael B. C. Khoo. Their work appears in journals such as IEEE Access, BMC Public Health and Quality of Life Research.
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.