D. Hansel
Impact in
- Statistical and Nonlinear Physics top 0.2%
- stochastic dynamics and bifurcation
- Cognitive Neuroscience top 0.5%
- Neural dynamics and brain function
Papers in
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- stochastic dynamics and bifurcation 14
- Complex Network Analysis Techniques 3
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- Neural dynamics and brain function 15
- Co-authors
- Germán Mato (7 shared papers)C. Meunier (3 shared papers)Haim Sompolinsky (3 shared papers)David Golomb (4 shared papers)Nicolas Brunel (3 shared papers)Carl van Vreeswijk (2 shared papers)Nicolas Brunel (1 shared paper)Nicolas Fourcaud‐Trocmé (1 shared paper)
In The Last Decade
D. Hansel
28 papers receiving 2.8k citations
Peers
Comparison fields: 5 of 106
- Statistical and Nonlinear Physics 1.5k
- Cognitive Neuroscience 2.3k
- Cellular and Molecular Neuroscience 1.1k
- Computer Networks and Communications 1.2k
- Condensed Matter Physics 129
Countries citing papers authored by D. Hansel
This map shows the geographic impact of D. Hansel'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 D. Hansel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites D. Hansel more than expected).
Fields of papers citing papers by D. Hansel
This network shows the impact of papers produced by D. Hansel. 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 D. Hansel. The network helps show where D. Hansel may publish in the future.
Co-authors
The 25 scholars most cited alongside D. Hansel, 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 28 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1995 | 454 | |
| 2 | 2003 | 407 | |
| 3 | 1992 | 247 | |
| 4 | 1993 | 228 | |
| 5 | 1992 | 220 | |
| 6 | 2005 | 219 | |
| 7 | 1998 | 140 | |
| 8 | 2000 | 135 | |
| 9 | 2003 | 133 | |
| 10 | 2003 | 117 | |
| 11 | 2001 | 113 | |
| 12 | 2006 | 105 | |
| 13 | 1987 | 89 | |
| 14 | 2005 | 86 | |
| 15 | 2006 | 85 | |
| 16 | 1992 | 78 | |
| 17 | 2001 | 53 | |
| 18 | 1985 | 24 | |
| 19 | 1993 | 16 | |
| 20 | 1986 | 16 |
About D. Hansel
D. Hansel is a scholar working on Statistical and Nonlinear Physics, Cognitive Neuroscience, Condensed Matter Physics, Computer Networks and Communications and Cellular and Molecular Neuroscience, having authored 28 papers that have together received 3.0k indexed citations. Recurring topics across this work include Neural dynamics and brain function (15 papers), stochastic dynamics and bifurcation (14 papers), Theoretical and Computational Physics (11 papers), Nonlinear Dynamics and Pattern Formation (10 papers), Photoreceptor and optogenetics research (3 papers), Stochastic processes and statistical mechanics (3 papers), Quantum many-body systems (3 papers) and Complex Network Analysis Techniques (3 papers). The work is most often cited by research in Statistical and Nonlinear Physics (1.5k citations), Cognitive Neuroscience (2.3k citations), Cellular and Molecular Neuroscience (1.1k citations), Computer Networks and Communications (1.2k citations) and Condensed Matter Physics (129 citations). D. Hansel has collaborated with scholars based in France, Israel and Argentina. Frequent co-authors include Germán Mato, C. Meunier, Haim Sompolinsky, David Golomb, Nicolas Brunel, Carl van Vreeswijk, Nicolas Brunel, Nicolas Fourcaud‐Trocmé, Alex Roxin and Benjamin Pfeuty. Their work appears in journals such as Neural Computation, Physical Review A, Journal of Neuroscience, Physical Review Letters and Physica A Statistical Mechanics and its Applications.
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.