Jeff Moehlis
- Cognitive Neuroscience top 1%
- Statistical and Nonlinear Physics top 0.5%
- Computer Networks and Communications top 1%
- Cellular and Molecular Neuroscience top 2%
- Electrical and Electronic Engineering top 10%
- Co-authors
- Philip HolmesEric BrownJonathan D. CohenRafał BogaczDan WilsonT SmithBarry E. DeMartiniKimberly L. Turner
- Topics
- Neural dynamics and brain function (46 papers)Nonlinear Dynamics and Pattern Formation (40 papers)stochastic dynamics and bifurcation (30 papers)
- Journals
- Proceedings of the National Academy of SciencesPhysical Review LettersApplied Physics Letters
- Partner nations
- United StatesGermanyUnited Kingdom
In The Last Decade
Jeff Moehlis
113 papers receiving 4.3k citations
Hit Papers
Peers
Comparison fields: 5 of 144
- Cognitive Neuroscience 1.9k
- Statistical and Nonlinear Physics 1.2k
- Computer Networks and Communications 1.2k
- Cellular and Molecular Neuroscience 764
- Electrical and Electronic Engineering 630
Countries citing papers authored by Jeff Moehlis
This map shows the geographic impact of Jeff Moehlis'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 Jeff Moehlis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jeff Moehlis more than expected).
Fields of papers citing papers by Jeff Moehlis
This network shows the impact of papers produced by Jeff Moehlis. 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 Jeff Moehlis. The network helps show where Jeff Moehlis may publish in the future.
Co-authorship network of co-authors of Jeff Moehlis
This figure shows the co-authorship network connecting the top 25 collaborators of Jeff Moehlis. A scholar is included among the top collaborators of Jeff Moehlis 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 Jeff Moehlis. Jeff Moehlis 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 | 11 | |
| 3 | 14 | |
| 4 | 27 | |
| 5 | 18 | |
| 6 | 68 | |
| 7 | 32 | |
| 8 | 10 | |
| 9 | 21 | |
| 10 | 26 | |
| 11 | 10 | |
| 12 | 35 | |
| 13 | 6 | |
| 14 | 2 | |
| 15 | 34 | |
| 16 | 1 | |
| 17 | 7 | |
| 18 | 17 | |
| 19 | 16 | |
| 20 | 39 |
About Jeff Moehlis
Jeff Moehlis is a scholar working on Statistical and Nonlinear Physics, Cognitive Neuroscience and Computer Networks and Communications, having authored 115 papers that have together received 4.5k indexed citations. Recurring topics across this work include Neural dynamics and brain function (46 papers), Nonlinear Dynamics and Pattern Formation (40 papers) and stochastic dynamics and bifurcation (30 papers). The work is most often cited by research in General Decision Sciences (250 citations), Cognitive Neuroscience (1.9k citations) and Statistical and Nonlinear Physics (1.2k citations). Jeff Moehlis has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Philip Holmes, Eric Brown, Jonathan D. Cohen, Rafał Bogacz, Dan Wilson, T Smith, Barry E. DeMartini, Kimberly L. Turner, Holger Faisst and Igor Mezić. Their work appears in journals such as Proceedings of the National Academy of Sciences, Physical Review Letters and Applied Physics Letters.
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.