Md. Sakib Bin Alam
- Artificial Intelligence top 10%
- Computer Networks and Communications top 10%
- Computer Vision and Pattern Recognition top 10%
- Electrical and Electronic Engineering
- Information Systems top 10%
- Co-authors
- Shams Forruque AhmedAmir H. GandomiNazifa RafaMahtabin Rodela RozbuM. MofijurTaoseef IshtiakA. B. M. Shawkat AliShaila Afrin
- Topics
- IoT and Edge/Fog Computing (7 papers)Blockchain Technology Applications and Security (7 papers)COVID-19 diagnosis using AI (3 papers)
- Journals
- SHILAP Revista de lepidopterologíaIEEE AccessNeurocomputing
- Partner nations
- BangladeshAustraliaThailand
In The Last Decade
Md. Sakib Bin Alam
17 papers receiving 697 citations
Hit Papers
Peers
Comparison fields: 5 of 136
- Artificial Intelligence 194
- Computer Networks and Communications 113
- Computer Vision and Pattern Recognition 79
- Electrical and Electronic Engineering 73
- Information Systems 65
Countries citing papers authored by Md. Sakib Bin Alam
This map shows the geographic impact of Md. Sakib Bin Alam'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. Sakib Bin Alam with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Md. Sakib Bin Alam more than expected).
Fields of papers citing papers by Md. Sakib Bin Alam
This network shows the impact of papers produced by Md. Sakib Bin Alam. 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. Sakib Bin Alam. The network helps show where Md. Sakib Bin Alam may publish in the future.
Co-authorship network of co-authors of Md. Sakib Bin Alam
This figure shows the co-authorship network connecting the top 25 collaborators of Md. Sakib Bin Alam. A scholar is included among the top collaborators of Md. Sakib Bin Alam 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. Sakib Bin Alam. Md. Sakib Bin Alam 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 | 2 | |
| 3 | 2 | |
| 4 | 2 | |
| 5 | 0 | |
| 6 | 9 | |
| 7 | 1 | |
| 8 | 5 | |
| 9 | 8 | |
| 10 | 7 | |
| 11 | 0 | |
| 12 | Toward a Secure 5G-Enabled Internet of Things: A Survey on Requirements, Privacy, Security, Challenges, and Opportunitiesbreakdown → | 49 |
| 13 | Deep learning modelling techniques: current progress, applications, advantages, and challengesbreakdown → | 412 |
| 14 | 71 | |
| 15 | 0 | |
| 16 | Insights into Internet of Medical Things (IoMT): Data fusion, security issues and potential solutionsbreakdown → | 106 |
| 17 | 15 | |
| 18 | 32 | |
| 19 | 6 | |
| 20 | Cloud Computing – Architecture, Platform and Security Issues: A Survey | 2 |
About Md. Sakib Bin Alam
Md. Sakib Bin Alam is a scholar working on Health Informatics, Medical Laboratory Technology and Information Systems, having authored 20 papers that have together received 731 indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (7 papers), Blockchain Technology Applications and Security (7 papers) and COVID-19 diagnosis using AI (3 papers). The work is most often cited by research in Health Informatics (17 citations), Health Information Management (31 citations) and Artificial Intelligence (194 citations). Md. Sakib Bin Alam has collaborated with scholars based in Bangladesh, Australia and Thailand. Frequent co-authors include Shams Forruque Ahmed, Amir H. Gandomi, Nazifa Rafa, Mahtabin Rodela Rozbu, M. Mofijur, Taoseef Ishtiak, A. B. M. Shawkat Ali, Shaila Afrin, Maliha Kabir and S. M. Muyeen. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Access and Neurocomputing.
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.