Nima Dehmamy
Impact in
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- Complex Network Analysis Techniques
- Opinion Dynamics and Social Influence
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- scientometrics and bibliometrics research
Papers in
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- Adversarial Robustness in Machine Learning 1
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- Data Visualization and Analytics 2
- Co-authors
- Albert-László Barabási (4 shared papers)Dashun Wang (1 shared paper)C. Lee Giles (1 shared paper)Rose Yu (2 shared papers)Sergey V. Buldyrev (2 shared papers)Irena Vodenska (2 shared papers)H. Eugene Stanley (1 shared paper)Shlomo Havlin (1 shared paper)
- Journals
- Nature Communications (1 paper)Nature Physics (1 paper)Nature (1 paper)Stereotactic and Functional Neurosurgery (1 paper)ACM Transactions on Interactive Intelligent Systems (1 paper)
- Partner nations
- United StatesAustriaIran
In The Last Decade
Nima Dehmamy
9 papers receiving 167 citations
Peers
Comparison fields: 5 of 74
- Statistical and Nonlinear Physics 55
- Statistics, Probability and Uncertainty 21
- Experimental and Cognitive Psychology 16
- Computer Vision and Pattern Recognition 21
- Cognitive Neuroscience 17
Countries citing papers authored by Nima Dehmamy
This map shows the geographic impact of Nima Dehmamy'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 Nima Dehmamy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nima Dehmamy more than expected).
Fields of papers citing papers by Nima Dehmamy
This network shows the impact of papers produced by Nima Dehmamy. 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 Nima Dehmamy. The network helps show where Nima Dehmamy may publish in the future.
Co-authors
The 19 scholars most cited alongside Nima Dehmamy, 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 | 2018 | 57 | |
| 2 | 2021 | 47 | |
| 3 | 2020 | 26 | |
| 4 | Understanding the Representation Power of Graph Neural Networks in Learning Graph Topology | 2019 | 14 |
| 5 | 2023 | 10 | |
| 6 | A Systemic Stress Test Model in Bank-Asset Networks | 2014 | 7 |
| 7 | 2021 | 7 | |
| 8 | Modelling Axon Growth Using Driven Diffusion | 2019 | 1 |
| 9 | 2019 | 1 | |
| 10 | 2025 | 0 | |
| 11 | 2025 | 0 | |
| 12 | 2024 | 0 |
About Nima Dehmamy
Nima Dehmamy is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Sociology and Political Science, Statistical and Nonlinear Physics and Finance, having authored 12 papers that have together received 170 indexed citations. Recurring topics across this work include Banking stability, regulation, efficiency (2 papers), Data Visualization and Analytics (2 papers), Complex Network Analysis Techniques (2 papers), Complex Systems and Time Series Analysis (2 papers), Topological and Geometric Data Analysis (1 paper), Computational and Text Analysis Methods (1 paper), Neurological disorders and treatments (1 paper) and Adversarial Robustness in Machine Learning (1 paper). The work is most often cited by research in Statistical and Nonlinear Physics (55 citations), Statistics, Probability and Uncertainty (21 citations), Experimental and Cognitive Psychology (16 citations), Computer Vision and Pattern Recognition (21 citations) and Cognitive Neuroscience (17 citations). Nima Dehmamy has collaborated with scholars based in United States, Austria and Iran. Frequent co-authors include Albert-László Barabási, Dashun Wang, C. Lee Giles, Rose Yu, Sergey V. Buldyrev, Irena Vodenska, H. Eugene Stanley, Shlomo Havlin, Shlomo Havlin and Daniel Haehn. Their work appears in journals such as Nature Communications, Nature Physics, Nature, Stereotactic and Functional Neurosurgery and ACM Transactions on Interactive Intelligent Systems.
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.