Ayan Chatterjee
Impact in
- Health Informatics top 5%
-
- Artificial Intelligence in Healthcare
Papers in
-
- Non-Invasive Vital Sign Monitoring 8
- Co-authors
- Martin Gerdes (11 shared papers)Santiago Martínez (10 shared papers)Andreas Prinz (16 shared papers)Bikas K. Chakrabarti (1 shared paper)Michael A. Riegler (9 shared papers)Banasri Hazra (2 shared papers)Yogesh Kumar Meena (2 shared papers)Debayan Das (5 shared papers)
- Journals
- Scientific Reports (5 papers)Tetrahedron (5 papers)IEEE Access (4 papers)Sensors (4 papers)Journal of Medical Internet Research (3 papers)
- Partner nations
- IndiaNorwayUnited States
In The Last Decade
Ayan Chatterjee
65 papers receiving 815 citations
Peers
Comparison fields: 5 of 138
- Health Informatics 24
- Health Information Management 79
- Applied Psychology 44
- Modeling and Simulation 30
- General Health Professions 141
Countries citing papers authored by Ayan Chatterjee
This map shows the geographic impact of Ayan Chatterjee'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 Ayan Chatterjee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ayan Chatterjee more than expected).
Fields of papers citing papers by Ayan Chatterjee
This network shows the impact of papers produced by Ayan Chatterjee. 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 Ayan Chatterjee. The network helps show where Ayan Chatterjee may publish in the future.
Co-authors
The 25 scholars most cited alongside Ayan Chatterjee, 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 78 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 131 | |
| 2 | Kinetic Exchange Models for Income and Wealth Distributions | 2012 | 99 |
| 3 | 2021 | 86 | |
| 4 | 2020 | 61 | |
| 5 | 2018 | 33 | |
| 6 | 2022 | 32 | |
| 7 | 2021 | 29 | |
| 8 | 1970 | 26 | |
| 9 | 2021 | 24 | |
| 10 | 2022 | 19 | |
| 11 | 2022 | 19 | |
| 12 | 1980 | 19 | |
| 13 | 2019 | 19 | |
| 14 | 2023 | 18 | |
| 15 | 2022 | 16 | |
| 16 | 2022 | 16 | |
| 17 | 2023 | 14 | |
| 18 | 2023 | 10 | |
| 19 | 2016 | 10 | |
| 20 | 1973 | 10 |
About Ayan Chatterjee
Ayan Chatterjee is a scholar working on Organic Chemistry, Biomedical Engineering, Computer Networks and Communications, Computer Vision and Pattern Recognition and Molecular Biology, having authored 78 papers that have together received 855 indexed citations. Recurring topics across this work include Non-Invasive Vital Sign Monitoring (8 papers), Context-Aware Activity Recognition Systems (7 papers), Mobile Health and mHealth Applications (6 papers), IoT and Edge/Fog Computing (5 papers), Heart Rate Variability and Autonomic Control (5 papers), ECG Monitoring and Analysis (5 papers), Opinion Dynamics and Social Influence (5 papers) and Complex Network Analysis Techniques (4 papers). The work is most often cited by research in Health Informatics (24 citations), Health Information Management (79 citations), Applied Psychology (44 citations), Modeling and Simulation (30 citations) and General Health Professions (141 citations). Ayan Chatterjee has collaborated with scholars based in India, Norway and United States. Frequent co-authors include Martin Gerdes, Santiago Martínez, Andreas Prinz, Bikas K. Chakrabarti, Michael A. Riegler, Banasri Hazra, Yogesh Kumar Meena, Debayan Das, Mrinal Kanti Naskar and Frank Y. Li. Their work appears in journals such as Scientific Reports, Tetrahedron, IEEE Access, Sensors and Journal of Medical Internet Research.
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.