Pavitra Krishnaswamy
- Health Informatics top 10%
- Cognitive Neuroscience top 10%
- EEG and Brain-Computer Interfaces 4
- Functional Brain Connectivity Studies 4
-
- COVID-19 diagnosis using AI 4
- Advanced MRI Techniques and Applications 3
-
- Topic Modeling 5
- Speech and dialogue systems 4
- Machine Learning in Healthcare 4
- AI in cancer detection 3
- Co-authors
- Hugh HerrEmery N. BrownPatrick L. PurdonJyrki AhveninenBehtash BabadiSheraz KhanMatti HämäläinenJuan Eugenio Iglesias
- Journals
- Proceedings of the National Academy of Sciences (1 paper)NeuroImage (1 paper)Philosophical Transactions of the Royal Society B Biological Sciences (1 paper)
- Partner nations
- SingaporeUnited StatesUnited Kingdom
In The Last Decade
Pavitra Krishnaswamy
21 papers receiving 311 citations
Peers
Comparison fields: 5 of 71
- Health Informatics 17
- Cognitive Neuroscience 142
- Biomedical Engineering 119
- Radiology, Nuclear Medicine and Imaging 53
- Signal Processing 18
Countries citing papers authored by Pavitra Krishnaswamy
This map shows the geographic impact of Pavitra Krishnaswamy'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 Pavitra Krishnaswamy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pavitra Krishnaswamy more than expected).
Fields of papers citing papers by Pavitra Krishnaswamy
This network shows the impact of papers produced by Pavitra Krishnaswamy. 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 Pavitra Krishnaswamy. The network helps show where Pavitra Krishnaswamy may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Pavitra Krishnaswamy, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2025 | 3 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 1 | |
| 7 | 2023 | 0 | |
| 8 | 2023 | 11 | |
| 9 | 2022 | 11 | |
| 10 | 2022 | 4 | |
| 11 | 2021 | 8 | |
| 12 | A Vital Signs Telemonitoring Programme Improves the Dynamic Prediction of Readmission Risk in Patients with Heart Failure. | 2020 | 3 |
| 13 | 2019 | 13 | |
| 14 | 2018 | 4 | |
| 15 | 2017 | 103 | |
| 16 | Reference-free removal of EEG-fMRI ballistocardiogram artifacts with harmonic regression | 2015 | 6 |
| 17 | 2015 | 17 | |
| 18 | 2013 | 8 | |
| 19 | 2011 | 67 | |
| 20 | 2011 | 46 |
About Pavitra Krishnaswamy
Pavitra Krishnaswamy is a scholar working on Health Informatics, Family Practice and Artificial Intelligence, having authored 23 papers that have together received 315 indexed citations. Recurring topics across this work include Topic Modeling (5 papers), Speech and dialogue systems (4 papers), Machine Learning in Healthcare (4 papers), EEG and Brain-Computer Interfaces (4 papers), Functional Brain Connectivity Studies (4 papers), COVID-19 diagnosis using AI (4 papers), AI in cancer detection (3 papers) and Advanced MRI Techniques and Applications (3 papers). The work is most often cited by research in Health Informatics (17 citations), Cognitive Neuroscience (142 citations) and Biomedical Engineering (119 citations). Pavitra Krishnaswamy has collaborated with scholars based in Singapore, United States and United Kingdom. Frequent co-authors include Hugh Herr, Emery N. Brown, Patrick L. Purdon, Jyrki Ahveninen, Behtash Babadi, Sheraz Khan, Matti Hämäläinen, Juan Eugenio Iglesias, J. Markowitz and Michael Frederick Eilenberg. Their work appears in journals such as Proceedings of the National Academy of Sciences, NeuroImage and Philosophical Transactions of the Royal Society B Biological Sciences.
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.