Iris Ginzburg
Impact in
- Cognitive Neuroscience top 2%
- Neural dynamics and brain function
- Memory and Neural Mechanisms
- Sleep and Wakefulness Research
- Visual perception and processing mechanisms
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- Neuroscience and Neuropharmacology Research
- Neuroscience and Neural Engineering
Papers in
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- Neural dynamics and brain function 2
- Memory and Neural Mechanisms 1
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- Nonlinear Dynamics and Pattern Formation 1
- Co-authors
- Bruce L. McNaughton (1 shared paper)Terrence J. Sejnowski (1 shared paper)Kechen Zhang (1 shared paper)Haim Sompolinsky (1 shared paper)D. Horn (1 shared paper)David Elad (1 shared paper)
- Journals
- Journal of Neurophysiology (1 paper)International Applied Mechanics (1 paper)Neural Information Processing Systems (1 paper)Journal of Biomedical Engineering (1 paper)Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics (1 paper)
- Partner nations
- United StatesIsrael
In The Last Decade
Iris Ginzburg
4 papers receiving 700 citations
Peers
Comparison fields: 5 of 72
- Cognitive Neuroscience 612
- Cellular and Molecular Neuroscience 390
- Statistical and Nonlinear Physics 97
- Sensory Systems 28
- Behavioral Neuroscience 13
Countries citing papers authored by Iris Ginzburg
This map shows the geographic impact of Iris Ginzburg'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 Iris Ginzburg with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Iris Ginzburg more than expected).
Fields of papers citing papers by Iris Ginzburg
This network shows the impact of papers produced by Iris Ginzburg. 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 Iris Ginzburg. The network helps show where Iris Ginzburg may publish in the future.
Co-authors
The 6 scholars most cited alongside Iris Ginzburg, 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 | 1998 | 498 | |
| 2 | 1994 | 153 | |
| 3 | Combined Neural Networks for Time Series Analysis | 1993 | 52 |
| 4 | 1993 | 17 | |
| 5 | 1967 | 0 |
About Iris Ginzburg
Iris Ginzburg is a scholar working on Cognitive Neuroscience, Computer Networks and Communications, Cellular and Molecular Neuroscience, Pulmonary and Respiratory Medicine and Statistical and Nonlinear Physics, having authored 5 papers that have together received 720 indexed citations. Recurring topics across this work include Neural dynamics and brain function (2 papers), Quantum, superfluid, helium dynamics (1 paper), Nonlinear Dynamics and Pattern Formation (1 paper), Memory and Neural Mechanisms (1 paper), Elasticity and Wave Propagation (1 paper), Advanced Theoretical and Applied Studies in Material Sciences and Geometry (1 paper), Geotechnical and Geomechanical Engineering (1 paper) and Neuroscience and Neuropharmacology Research (1 paper). The work is most often cited by research in Cognitive Neuroscience (612 citations), Cellular and Molecular Neuroscience (390 citations), Statistical and Nonlinear Physics (97 citations), Sensory Systems (28 citations) and Behavioral Neuroscience (13 citations). Iris Ginzburg has collaborated with scholars based in United States and Israel. Frequent co-authors include Bruce L. McNaughton, Terrence J. Sejnowski, Kechen Zhang, Haim Sompolinsky, D. Horn and David Elad. Their work appears in journals such as Journal of Neurophysiology, International Applied Mechanics, Neural Information Processing Systems, Journal of Biomedical Engineering and Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.
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.