Uzzal Kumar Acharjee
Impact in
- Signal Processing top 10%
- Advanced Malware Detection Techniques
Papers in
-
- AI in cancer detection 5
- Co-authors
- Md. Ashraf Uddin (10 shared papers)Md. Manowarul Islam (5 shared papers)Selina Sharmin (3 shared papers)Shaoen Wu (1 shared paper)Md. Jahidul Islam (1 shared paper)Shahab S. Band (1 shared paper)Md. Razaul Karim (1 shared paper)Anichur Rahman (1 shared paper)
- Journals
- Journal of Biomolecular Structure and Dynamics (3 papers)Cybersecurity (2 papers)Scientific Reports (1 paper)Electronics (1 paper)IEEE Access (1 paper)
- Partner nations
- BangladeshAustraliaSaudi Arabia
In The Last Decade
Uzzal Kumar Acharjee
37 papers receiving 471 citations
Peers
Comparison fields: 5 of 107
- Signal Processing 56
- Health Informatics 7
- Artificial Intelligence 159
- Computer Networks and Communications 111
- Information Systems 105
Countries citing papers authored by Uzzal Kumar Acharjee
This map shows the geographic impact of Uzzal Kumar Acharjee'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 Uzzal Kumar Acharjee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Uzzal Kumar Acharjee more than expected).
Fields of papers citing papers by Uzzal Kumar Acharjee
This network shows the impact of papers produced by Uzzal Kumar Acharjee. 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 Uzzal Kumar Acharjee. The network helps show where Uzzal Kumar Acharjee may publish in the future.
Co-authors
The 25 scholars most cited alongside Uzzal Kumar Acharjee, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 95 | |
| 2 | 2020 | 55 | |
| 3 | 2023 | 38 | |
| 4 | 2021 | 36 | |
| 5 | 2020 | 33 | |
| 6 | 2022 | 23 | |
| 7 | 2020 | 18 | |
| 8 | 2021 | 18 | |
| 9 | 2022 | 17 | |
| 10 | 2024 | 15 | |
| 11 | 2021 | 14 | |
| 12 | 2019 | 14 | |
| 13 | 2023 | 13 | |
| 14 | 2023 | 12 | |
| 15 | 2020 | 12 | |
| 16 | 2021 | 10 | |
| 17 | 2023 | 7 | |
| 18 | 2020 | 7 | |
| 19 | 2018 | 6 | |
| 20 | 2015 | 5 |
About Uzzal Kumar Acharjee
Uzzal Kumar Acharjee is a scholar working on Artificial Intelligence, Molecular Biology, Information Systems, Computational Theory and Mathematics and Radiology, Nuclear Medicine and Imaging, having authored 41 papers that have together received 488 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (5 papers), AI in cancer detection (5 papers), COVID-19 diagnosis using AI (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Long-Term Effects of COVID-19 (2 papers), Plant Pathogens and Fungal Diseases (2 papers), Nonlinear Optical Materials Studies (2 papers) and IoT and Edge/Fog Computing (2 papers). The work is most often cited by research in Signal Processing (56 citations), Health Informatics (7 citations), Artificial Intelligence (159 citations), Computer Networks and Communications (111 citations) and Information Systems (105 citations). Uzzal Kumar Acharjee has collaborated with scholars based in Bangladesh, Australia and Saudi Arabia. Frequent co-authors include Md. Ashraf Uddin, Md. Manowarul Islam, Selina Sharmin, Shaoen Wu, Md. Jahidul Islam, Shahab S. Band, Md. Razaul Karim, Anichur Rahman, Mehdi Sookhak and Mostofa Kamal Nasir. Their work appears in journals such as Journal of Biomolecular Structure and Dynamics, Cybersecurity, Scientific Reports, Electronics and IEEE Access.
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.