Pushpendra Singh
Impact in
- Cognitive Neuroscience top 5%
- EEG and Brain-Computer Interfaces
- Signal Processing top 2%
- Blind Source Separation Techniques
Papers in
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- Blind Source Separation Techniques 12
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- EEG and Brain-Computer Interfaces 14
- Co-authors
- Amit Singhal (22 shared papers)Ram Bilas Pachori (7 shared papers)Binish Fatimah (15 shared papers)Anubha Gupta (15 shared papers)Shiv Dutt Joshi (15 shared papers)Brejesh Lall (3 shared papers)Kaushik Saha (3 shared papers)Priya Aggarwal (3 shared papers)
- Journals
- Biomedical Signal Processing and Control (3 papers)Computer Vision and Image Understanding (2 papers)Computers in Biology and Medicine (2 papers)Digital Signal Processing (2 papers)Journal of Applied Biomedicine (2 papers)
- Partner nations
- IndiaUnited StatesUnited Kingdom
In The Last Decade
Pushpendra Singh
48 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 108
- Cognitive Neuroscience 565
- Signal Processing 294
- Modeling and Simulation 108
- Cardiology and Cardiovascular Medicine 383
- Health Informatics 16
Countries citing papers authored by Pushpendra Singh
This map shows the geographic impact of Pushpendra Singh'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 Pushpendra Singh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pushpendra Singh more than expected).
Fields of papers citing papers by Pushpendra Singh
This network shows the impact of papers produced by Pushpendra Singh. 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 Pushpendra Singh. The network helps show where Pushpendra Singh may publish in the future.
Co-authors
The 25 scholars most cited alongside Pushpendra Singh, 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 57 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 139 | |
| 2 | 2019 | 123 | |
| 3 | 2020 | 101 | |
| 4 | 2022 | 100 | |
| 5 | 2020 | 85 | |
| 6 | 2017 | 63 | |
| 7 | 2021 | 56 | |
| 8 | 2015 | 54 | |
| 9 | 2021 | 52 | |
| 10 | 2021 | 50 | |
| 11 | 2018 | 46 | |
| 12 | 2021 | 46 | |
| 13 | 2020 | 44 | |
| 14 | 2022 | 42 | |
| 15 | 2021 | 40 | |
| 16 | 2022 | 33 | |
| 17 | 2022 | 22 | |
| 18 | 2017 | 21 | |
| 19 | 2013 | 21 | |
| 20 | 2014 | 21 |
About Pushpendra Singh
Pushpendra Singh is a scholar working on Signal Processing, Cognitive Neuroscience, Computer Vision and Pattern Recognition, Cardiology and Cardiovascular Medicine and Artificial Intelligence, having authored 57 papers that have together received 1.3k indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (14 papers), Blind Source Separation Techniques (12 papers), ECG Monitoring and Analysis (10 papers), Image and Signal Denoising Methods (8 papers), COVID-19 epidemiological studies (5 papers), Machine Fault Diagnosis Techniques (5 papers), COVID-19 diagnosis using AI (5 papers) and Advanced Electrical Measurement Techniques (4 papers). The work is most often cited by research in Cognitive Neuroscience (565 citations), Signal Processing (294 citations), Modeling and Simulation (108 citations), Cardiology and Cardiovascular Medicine (383 citations) and Health Informatics (16 citations). Pushpendra Singh has collaborated with scholars based in India, United States and United Kingdom. Frequent co-authors include Amit Singhal, Ram Bilas Pachori, Binish Fatimah, Anubha Gupta, Shiv Dutt Joshi, Brejesh Lall, Kaushik Saha, Priya Aggarwal, Pranav Soman and Pradip Sircar. Their work appears in journals such as Biomedical Signal Processing and Control, Computer Vision and Image Understanding, Computers in Biology and Medicine, Digital Signal Processing and Journal of Applied Biomedicine.
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.