Deepak Iyer
- Health Informatics top 2%
- Computational Mathematics top 10%
- Condensed Matter Physics top 10%
- Physics of Superconductivity and Magnetism 3
- Theoretical and Computational Physics 3
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- Quantum many-body systems 10
- Cold Atom Physics and Bose-Einstein Condensates 9
- Quantum, superfluid, helium dynamics 3
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- Opinion Dynamics and Social Influence 3
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- Transplantation: Methods and Outcomes 2
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- Radiomics and Machine Learning in Medical Imaging 1
Deepak Iyer
21 papers receiving 492 citations
Peers
Comparison fields: 5 of 73
- Health Informatics 52
- Computational Mathematics 9
- Condensed Matter Physics 113
- Atomic and Molecular Physics, and Optics 264
- Statistical and Nonlinear Physics 86
Countries citing papers authored by Deepak Iyer
This map shows the geographic impact of Deepak Iyer'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 Deepak Iyer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Deepak Iyer more than expected).
Fields of papers citing papers by Deepak Iyer
This network shows the impact of papers produced by Deepak Iyer. 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 Deepak Iyer. The network helps show where Deepak Iyer may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Deepak Iyer, 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 | 2024 | 1 | |
| 2 | 2024 | 1 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 1 | |
| 5 | 2023 | 67 | |
| 6 | 2022 | 27 | |
| 7 | 2022 | 0 | |
| 8 | 2020 | 1 | |
| 9 | 2019 | 0 | |
| 10 | 2015 | 17 | |
| 11 | 2015 | 12 | |
| 12 | 2015 | 26 | |
| 13 | 2015 | 36 | |
| 14 | An exact formalism for quench dynamics | 2013 | 0 |
| 15 | Quench Dynamics of the Interacting Bose Gas in one Dimension | 2013 | 1 |
| 16 | 2013 | 1 | |
| 17 | 2013 | 50 | |
| 18 | 2012 | 68 | |
| 19 | 2003 | 42 | |
| 20 | 2003 | 70 |
About Deepak Iyer
Deepak Iyer is a scholar working on Health Informatics, Condensed Matter Physics, Atomic and Molecular Physics, and Optics, Statistical and Nonlinear Physics and Internal Medicine, having authored 26 papers that have together received 511 indexed citations. Recurring topics across this work include Quantum many-body systems (10 papers), Cold Atom Physics and Bose-Einstein Condensates (9 papers), Quantum, superfluid, helium dynamics (3 papers), Physics of Superconductivity and Magnetism (3 papers), Opinion Dynamics and Social Influence (3 papers), Theoretical and Computational Physics (3 papers), Transplantation: Methods and Outcomes (2 papers) and Radiomics and Machine Learning in Medical Imaging (1 paper). The work is most often cited by research in Health Informatics (52 citations), Computational Mathematics (9 citations), Condensed Matter Physics (113 citations), Atomic and Molecular Physics, and Optics (264 citations) and Statistical and Nonlinear Physics (86 citations). Deepak Iyer has collaborated with scholars based in United States, India and Canada. Frequent co-authors include Natan Andrei, Marcos Rigol, Liviu Iftode, Faisal Sultan, K. Srinivasan, Lev Vidmar, Sebastian Will, Cristian Borcea, Porlin Kang and Hanzhou Li. Their work appears in journals such as Physical Review B, Physical Review Letters, The Journal of Heart and Lung Transplantation, Physical Review A and Nature Communications.
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.