Jay Pandit
Impact in
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- Heart Rate Variability and Autonomic Control
- Blood Pressure and Hypertension Studies
- Cardiovascular Health and Disease Prevention
Papers in
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- Heart Rate Variability and Autonomic Control 6
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- Mobile Health and mHealth Applications 3
- Co-authors
- Daniel Batlle (3 shared papers)Eric J. Topol (4 shared papers)Giorgio Quer (10 shared papers)Jennifer M. Radin (7 shared papers)Jeff Pawelek (4 shared papers)Bruce Leff (1 shared paper)Jan Wysocki (1 shared paper)Edward Ramos (6 shared papers)
- Journals
- npj Digital Medicine (2 papers)The Lancet Digital Health (2 papers)JAMA (2 papers)Circulation (1 paper)BMC Public Health (1 paper)
- Partner nations
- United StatesGermanyIsrael
In The Last Decade
Jay Pandit
29 papers receiving 467 citations
Peers
Comparison fields: 5 of 99
- Cardiology and Cardiovascular Medicine 121
- Health Informatics 6
- Infectious Diseases 56
- Biomedical Engineering 141
- Modeling and Simulation 14
Countries citing papers authored by Jay Pandit
This map shows the geographic impact of Jay Pandit'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 Jay Pandit with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jay Pandit more than expected).
Fields of papers citing papers by Jay Pandit
This network shows the impact of papers produced by Jay Pandit. 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 Jay Pandit. The network helps show where Jay Pandit may publish in the future.
Co-authors
The 25 scholars most cited alongside Jay Pandit, 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 31 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 78 | |
| 2 | 2020 | 70 | |
| 3 | 2022 | 56 | |
| 4 | 2024 | 36 | |
| 5 | 2020 | 32 | |
| 6 | 2010 | 27 | |
| 7 | 2023 | 23 | |
| 8 | 2023 | 21 | |
| 9 | 2022 | 19 | |
| 10 | 2022 | 16 | |
| 11 | 2022 | 14 | |
| 12 | 2015 | 13 | |
| 13 | 2015 | 12 | |
| 14 | 2006 | 11 | |
| 15 | 2024 | 10 | |
| 16 | 2025 | 8 | |
| 17 | 2023 | 8 | |
| 18 | 2024 | 6 | |
| 19 | 2024 | 5 | |
| 20 | 2024 | 4 |
About Jay Pandit
Jay Pandit is a scholar working on Cardiology and Cardiovascular Medicine, General Health Professions, Public Health, Environmental and Occupational Health, Biomedical Engineering and Molecular Biology, having authored 31 papers that have together received 484 indexed citations. Recurring topics across this work include Heart Rate Variability and Autonomic Control (6 papers), Mobile Health and mHealth Applications (3 papers), Non-Invasive Vital Sign Monitoring (3 papers), COVID-19 epidemiological studies (2 papers), COVID-19 Digital Contact Tracing (2 papers), Data-Driven Disease Surveillance (2 papers), Ethics in Clinical Research (2 papers) and Sleep and related disorders (2 papers). The work is most often cited by research in Cardiology and Cardiovascular Medicine (121 citations), Health Informatics (6 citations), Infectious Diseases (56 citations), Biomedical Engineering (141 citations) and Modeling and Simulation (14 citations). Jay Pandit has collaborated with scholars based in United States, Germany and Israel. Frequent co-authors include Daniel Batlle, Eric J. Topol, Giorgio Quer, Jennifer M. Radin, Jeff Pawelek, Bruce Leff, Jan Wysocki, Edward Ramos, Yiming Liu and Jacob Trueb. Their work appears in journals such as npj Digital Medicine, The Lancet Digital Health, JAMA, Circulation and BMC Public Health.
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.