Mohammed Diykh
Impact in
- Cognitive Neuroscience top 5%
- EEG and Brain-Computer Interfaces
- Sleep and Wakefulness Research
- Functional Brain Connectivity Studies
- Signal Processing top 2%
- Blind Source Separation Techniques
- Advanced Malware Detection Techniques
Papers in
-
- EEG and Brain-Computer Interfaces 19
-
- Blind Source Separation Techniques 9
- Co-authors
- Yan Li (8 shared papers)Shahab Abdulla (20 shared papers)Peng Wen (4 shared papers)Ravinesh C. Deo (7 shared papers)Jonathan H. Green (6 shared papers)David Lai (1 shared paper)Khalid Saleh (3 shared papers)Siuly Siuly (5 shared papers)
- Journals
- Expert Systems with Applications (6 papers)Biomedical Signal Processing and Control (3 papers)Computer Methods and Programs in Biomedicine (2 papers)IEEE Access (2 papers)Measurement (2 papers)
- Partner nations
- AustraliaIraqSouth Africa
In The Last Decade
Mohammed Diykh
25 papers receiving 821 citations
Peers
Comparison fields: 5 of 91
- Cognitive Neuroscience 557
- Signal Processing 285
- Human-Computer Interaction 48
- Experimental and Cognitive Psychology 87
- Cardiology and Cardiovascular Medicine 119
Countries citing papers authored by Mohammed Diykh
This map shows the geographic impact of Mohammed Diykh'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 Mohammed Diykh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mohammed Diykh more than expected).
Fields of papers citing papers by Mohammed Diykh
This network shows the impact of papers produced by Mohammed Diykh. 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 Mohammed Diykh. The network helps show where Mohammed Diykh may publish in the future.
Co-authors
The 16 scholars most cited alongside Mohammed Diykh, 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 28 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 122 | |
| 2 | 2017 | 100 | |
| 3 | 2020 | 75 | |
| 4 | 2016 | 71 | |
| 5 | 2017 | 71 | |
| 6 | 2016 | 59 | |
| 7 | 2019 | 50 | |
| 8 | 2019 | 47 | |
| 9 | 2020 | 34 | |
| 10 | 2019 | 24 | |
| 11 | 2021 | 21 | |
| 12 | 2018 | 21 | |
| 13 | 2022 | 21 | |
| 14 | 2023 | 19 | |
| 15 | 2017 | 19 | |
| 16 | 2023 | 16 | |
| 17 | 2019 | 15 | |
| 18 | 2022 | 15 | |
| 19 | 2022 | 15 | |
| 20 | 2022 | 9 |
About Mohammed Diykh
Mohammed Diykh is a scholar working on Cognitive Neuroscience, Signal Processing, Biomedical Engineering, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 28 papers that have together received 842 indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (19 papers), Blind Source Separation Techniques (9 papers), Non-Invasive Vital Sign Monitoring (3 papers), Advanced Chemical Sensor Technologies (3 papers), Gaze Tracking and Assistive Technology (3 papers), Optical Imaging and Spectroscopy Techniques (2 papers), Energy Load and Power Forecasting (2 papers) and Hydrological Forecasting Using AI (2 papers). The work is most often cited by research in Cognitive Neuroscience (557 citations), Signal Processing (285 citations), Human-Computer Interaction (48 citations), Experimental and Cognitive Psychology (87 citations) and Cardiology and Cardiovascular Medicine (119 citations). Mohammed Diykh has collaborated with scholars based in Australia, Iraq and South Africa. Frequent co-authors include Yan Li, Shahab Abdulla, Peng Wen, Ravinesh C. Deo, Jonathan H. Green, David Lai, Khalid Saleh, Siuly Siuly, Xiangkui Wan and Mumtaz Ali. Their work appears in journals such as Expert Systems with Applications, Biomedical Signal Processing and Control, Computer Methods and Programs in Biomedicine, IEEE Access and Measurement.
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.