Mohammad Zavid Parvez
- Cognitive Neuroscience top 5%
- Artificial Intelligence top 5%
- Radiology, Nuclear Medicine and Imaging top 5%
- Signal Processing top 5%
- Neurology top 5%
- Co-authors
- Manoranjan PaulAnisur RahmanMahmudul HasanTasmi TamannaIckjai LeeMd Tanzim RezaMohammed KaosarJia Uddin
- Topics
- EEG and Brain-Computer Interfaces (22 papers)Blind Source Separation Techniques (13 papers)Brain Tumor Detection and Classification (8 papers)
- Partner nations
- BangladeshAustraliaUnited States
In The Last Decade
Mohammad Zavid Parvez
42 papers receiving 934 citations
Hit Papers
Peers
Comparison fields: 5 of 82
- Cognitive Neuroscience 375
- Artificial Intelligence 369
- Radiology, Nuclear Medicine and Imaging 348
- Signal Processing 184
- Neurology 163
Countries citing papers authored by Mohammad Zavid Parvez
This map shows the geographic impact of Mohammad Zavid Parvez'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 Mohammad Zavid Parvez with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mohammad Zavid Parvez more than expected).
Fields of papers citing papers by Mohammad Zavid Parvez
This network shows the impact of papers produced by Mohammad Zavid Parvez. 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 Mohammad Zavid Parvez. The network helps show where Mohammad Zavid Parvez may publish in the future.
Co-authorship network of co-authors of Mohammad Zavid Parvez
This figure shows the co-authorship network connecting the top 25 collaborators of Mohammad Zavid Parvez. A scholar is included among the top collaborators of Mohammad Zavid Parvez 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 Mohammad Zavid Parvez. Mohammad Zavid Parvez is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 24 | |
| 4 | 1 | |
| 5 | 4 | |
| 6 | 63 | |
| 7 | 1 | |
| 8 | 24 | |
| 9 | 1 | |
| 10 | CoroDet: A deep learning based classification for COVID-19 detection using chest X-ray imagesbreakdown → | 322 |
| 11 | 11 | |
| 12 | 0 | |
| 13 | 2 | |
| 14 | 5 | |
| 15 | 0 | |
| 16 | 67 | |
| 17 | 2 | |
| 18 | 49 | |
| 19 | 12 | |
| 20 | 5 |
About Mohammad Zavid Parvez
Mohammad Zavid Parvez is a scholar working on Signal Processing, Cognitive Neuroscience and Neurology, having authored 46 papers that have together received 982 indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (22 papers), Blind Source Separation Techniques (13 papers) and Brain Tumor Detection and Classification (8 papers). The work is most often cited by research in Health Informatics (50 citations), Neurology (163 citations) and Cognitive Neuroscience (375 citations). Mohammad Zavid Parvez has collaborated with scholars based in Bangladesh, Australia and United States. Frequent co-authors include Manoranjan Paul, Anisur Rahman, Mahmudul Hasan, Tasmi Tamanna, Ickjai Lee, Md Tanzim Reza, Mohammed Kaosar, Jia Uddin, Mohammad Shorif Uddin and Kyriaki Kalimeri. Their work appears in journals such as IEEE Transactions on Biomedical Engineering, Neurocomputing and Chaos Solitons & Fractals.
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.