Ramakrishna Mukkamala
- Cardiology and Cardiovascular Medicine top 0.5%
- Biomedical Engineering top 0.5%
- Surgery top 1%
- Radiology, Nuclear Medicine and Imaging top 10%
- Cognitive Neuroscience top 10%
- Co-authors
- Jin‐Oh HahnChang‐Sei KimOmer T. InanRichard J. CohenLalit K. MesthaSurvi KyalHakan TöreyinKeerthana Natarajan
- Topics
- Non-Invasive Vital Sign Monitoring (93 papers)Heart Rate Variability and Autonomic Control (82 papers)Hemodynamic Monitoring and Therapy (79 papers)
- Partner nations
- United StatesTaiwanSouth Korea
In The Last Decade
Ramakrishna Mukkamala
143 papers receiving 3.7k citations
Hit Papers
Peers
Comparison fields: 5 of 114
- Cardiology and Cardiovascular Medicine 3.2k
- Biomedical Engineering 2.7k
- Surgery 2.0k
- Radiology, Nuclear Medicine and Imaging 188
- Cognitive Neuroscience 154
Countries citing papers authored by Ramakrishna Mukkamala
This map shows the geographic impact of Ramakrishna Mukkamala'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 Ramakrishna Mukkamala with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ramakrishna Mukkamala more than expected).
Fields of papers citing papers by Ramakrishna Mukkamala
This network shows the impact of papers produced by Ramakrishna Mukkamala. 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 Ramakrishna Mukkamala. The network helps show where Ramakrishna Mukkamala may publish in the future.
Co-authorship network of co-authors of Ramakrishna Mukkamala
This figure shows the co-authorship network connecting the top 25 collaborators of Ramakrishna Mukkamala. A scholar is included among the top collaborators of Ramakrishna Mukkamala based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ramakrishna Mukkamala. Ramakrishna Mukkamala is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 30 | |
| 3 | 3 | |
| 4 | 7 | |
| 5 | 4 | |
| 6 | 4 | |
| 7 | 15 | |
| 8 | 47 | |
| 9 | 38 | |
| 10 | 13 | |
| 11 | 147 | |
| 12 | 4 | |
| 13 | 43 | |
| 14 | 6 | |
| 15 | Forecasting acute hypotensive episodes in intensive care patients based on a peripheral arterial blood pressure waveform | 31 |
| 16 | 10 | |
| 17 | 1 | |
| 18 | 15 | |
| 19 | 32 | |
| 20 | A weighted principal component regression approach for system identification | 1 |
About Ramakrishna Mukkamala
Ramakrishna Mukkamala is a scholar working on Cardiology and Cardiovascular Medicine, Biomedical Engineering and Surgery, having authored 149 papers that have together received 3.8k indexed citations. Recurring topics across this work include Non-Invasive Vital Sign Monitoring (93 papers), Heart Rate Variability and Autonomic Control (82 papers) and Hemodynamic Monitoring and Therapy (79 papers). The work is most often cited by research in Cardiology and Cardiovascular Medicine (3.2k citations), Biomedical Engineering (2.7k citations) and Surgery (2.0k citations). Ramakrishna Mukkamala has collaborated with scholars based in United States, Taiwan and South Korea. Frequent co-authors include Jin‐Oh Hahn, Chang‐Sei Kim, Omer T. Inan, Richard J. Cohen, Lalit K. Mestha, Survi Kyal, Hakan Töreyin, Keerthana Natarajan, N. Bari Olivier and Anand Chandrasekhar. Their work appears in journals such as Scientific Reports, The FASEB Journal and Journal of Applied Physiology.
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.