Md Geaur Rahman
- Artificial Intelligence top 5%
- Information Systems top 10%
- Statistics and Probability top 5%
- Computer Vision and Pattern Recognition top 10%
- Management Science and Operations Research top 10%
- Co-authors
- Md Zahidul IslamJunbin GaoTerry BossomaierSabih ur RehmanMinh ChauMd. Akhtaruzzaman KhanQuazi MamunHadi Eskandari
- Topics
- Data Mining Algorithms and Applications (6 papers)Statistical Methods and Inference (3 papers)Machine Learning and Data Classification (3 papers)
- Partner nations
- AustraliaBangladeshUnited States
In The Last Decade
Md Geaur Rahman
15 papers receiving 336 citations
Peers
Comparison fields: 5 of 79
- Artificial Intelligence 229
- Information Systems 100
- Statistics and Probability 77
- Computer Vision and Pattern Recognition 70
- Management Science and Operations Research 55
Countries citing papers authored by Md Geaur Rahman
This map shows the geographic impact of Md Geaur Rahman'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 Md Geaur Rahman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Md Geaur Rahman more than expected).
Fields of papers citing papers by Md Geaur Rahman
This network shows the impact of papers produced by Md Geaur Rahman. 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 Md Geaur Rahman. The network helps show where Md Geaur Rahman may publish in the future.
Co-authorship network of co-authors of Md Geaur Rahman
This figure shows the co-authorship network connecting the top 25 collaborators of Md Geaur Rahman. A scholar is included among the top collaborators of Md Geaur Rahman 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 Md Geaur Rahman. Md Geaur Rahman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 1 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 4 | |
| 6 | Reframing in Clustering: An Introductory Survey | 0 |
| 7 | 59 | |
| 8 | 27 | |
| 9 | Data Cleansing During Data Collection from Wireless Sensor Networks | 4 |
| 10 | 10 | |
| 11 | 43 | |
| 12 | 106 | |
| 13 | Data Quality Improvement by Imputation of Missing Values | 7 |
| 14 | A Novel Framework Using Two Layers of Missing Value Imputation | 2 |
| 15 | 20 | |
| 16 | 65 |
About Md Geaur Rahman
Md Geaur Rahman is a scholar working on Statistics and Probability, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 16 papers that have together received 355 indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (6 papers), Statistical Methods and Inference (3 papers) and Machine Learning and Data Classification (3 papers). The work is most often cited by research in Statistics and Probability (77 citations), Artificial Intelligence (229 citations) and Information Systems (100 citations). Md Geaur Rahman has collaborated with scholars based in Australia, Bangladesh and United States. Frequent co-authors include Md Zahidul Islam, Junbin Gao, Terry Bossomaier, Sabih ur Rehman, Minh Chau, Md. Akhtaruzzaman Khan, Quazi Mamun, Hadi Eskandari, Tofael Ahamed and David A. Fleming. Their work appears in journals such as Expert Systems with Applications, IEEE Access and Knowledge-Based Systems.
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.