Mahmudul Hasan
- Radiology, Nuclear Medicine and Imaging top 5%
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 10%
- Materials Chemistry
- Neurology top 10%
- Co-authors
- Anisur RahmanMohammad Zavid ParvezIckjai LeeTasmi TamannaPınar AcarYousef HaseliOliver GutfleischJürgen Gassmann
- Topics
- Machine Learning in Materials Science (7 papers)Advancements in Semiconductor Devices and Circuit Design (4 papers)Thermochemical Biomass Conversion Processes (4 papers)
- Partner nations
- United StatesBangladeshAustralia
In The Last Decade
Mahmudul Hasan
29 papers receiving 584 citations
Hit Papers
Peers
Comparison fields: 5 of 94
- Radiology, Nuclear Medicine and Imaging 311
- Artificial Intelligence 233
- Computer Vision and Pattern Recognition 74
- Materials Chemistry 67
- Neurology 67
Countries citing papers authored by Mahmudul Hasan
This map shows the geographic impact of Mahmudul Hasan'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 Mahmudul Hasan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mahmudul Hasan more than expected).
Fields of papers citing papers by Mahmudul Hasan
This network shows the impact of papers produced by Mahmudul Hasan. 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 Mahmudul Hasan. The network helps show where Mahmudul Hasan may publish in the future.
Co-authorship network of co-authors of Mahmudul Hasan
This figure shows the co-authorship network connecting the top 25 collaborators of Mahmudul Hasan. A scholar is included among the top collaborators of Mahmudul Hasan 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 Mahmudul Hasan. Mahmudul Hasan 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 | 0 | |
| 3 | 4 | |
| 4 | 14 | |
| 5 | 1 | |
| 6 | 0 | |
| 7 | 12 | |
| 8 | 0 | |
| 9 | 21 | |
| 10 | 0 | |
| 11 | 3 | |
| 12 | 1 | |
| 13 | 3 | |
| 14 | 15 | |
| 15 | CoroDet: A deep learning based classification for COVID-19 detection using chest X-ray imagesbreakdown → | 322 |
| 16 | 1 | |
| 17 | 40 | |
| 18 | 12 | |
| 19 | 6 | |
| 20 | Development of Automatic Smart Waste Sorter Machine | 20 |
About Mahmudul Hasan
Mahmudul Hasan is a scholar working on Metals and Alloys, Process Chemistry and Technology and General Materials Science, having authored 35 papers that have together received 608 indexed citations. Recurring topics across this work include Machine Learning in Materials Science (7 papers), Advancements in Semiconductor Devices and Circuit Design (4 papers) and Thermochemical Biomass Conversion Processes (4 papers). The work is most often cited by research in Health Informatics (38 citations), Radiology, Nuclear Medicine and Imaging (311 citations) and Neurology (67 citations). Mahmudul Hasan has collaborated with scholars based in United States, Bangladesh and Australia. Frequent co-authors include Anisur Rahman, Mohammad Zavid Parvez, Ickjai Lee, Tasmi Tamanna, Pınar Acar, Yousef Haseli, Oliver Gutfleisch, Jürgen Gassmann, Sabbir A. Khan and Sharif Mohammad Mominuzzaman. Their work appears in journals such as Journal of the American Chemical Society, Acta Materialia and Scientific Reports.
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.