David Cai

3.3k citations
107 papers · 2.4k · h-index 28

Impact in

Papers in

David Cai

105 papers receiving 2.3k citations

Peers

David Cai
Comparison fields: 5 of 127
  • Statistical and Nonlinear Physics 1.2k
  • Cognitive Neuroscience 737
  • Cellular and Molecular Neuroscience 335
  • Atomic and Molecular Physics, and Optics 562
  • Computer Networks and Communications 400
Replace Alessandro Torcini with:
Alessandro Torcini Italy
Elisha Moses Israel
John C. Neu United States
William L. Kath United States
Arun V. Holden United Kingdom
Juan A. Acebrón Spain
Renato Spigler Italy
Igor Goychuk Germany
V. N. Biktashev United Kingdom
C. J. Pérez Vicente Spain
David Cai relative to Alessandro Torcini Italy Alessandro Torcini's profile →
Citations per field
00.5×1.6×
Alessandro Torcini · 1×
Citations per year

Countries citing papers authored by David Cai

Since Specialization
Citations

This map shows the geographic impact of David Cai'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 David Cai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Cai more than expected).

Fields of papers citing papers by David Cai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David Cai. 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 David Cai. The network helps show where David Cai may publish in the future.

Co-authors

The 25 scholars most cited alongside David Cai, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with David Cai Line = papers co-authored together David Cai links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 107 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012182
2 1994143
3 201397
4 200487
5 200180
6 200275
7 199568
8 200662
9 200553
10 199652
11 199951
12 200550
13 200549
14 200640
15 199638
16 201837
17 201036
18 199533
19 201033
20 201333

About David Cai

David Cai is a scholar working on Statistical and Nonlinear Physics, Cognitive Neuroscience, Cellular and Molecular Neuroscience, Atomic and Molecular Physics, and Optics and Computer Networks and Communications, having authored 107 papers that have together received 2.4k indexed citations. Recurring topics across this work include Neural dynamics and brain function (47 papers), Nonlinear Photonic Systems (28 papers), stochastic dynamics and bifurcation (23 papers), Nonlinear Dynamics and Pattern Formation (18 papers), Advanced Fiber Laser Technologies (17 papers), Nonlinear Waves and Solitons (12 papers), Neuroscience and Neural Engineering (11 papers) and Photoreceptor and optogenetics research (9 papers). The work is most often cited by research in Statistical and Nonlinear Physics (1.2k citations), Cognitive Neuroscience (737 citations), Cellular and Molecular Neuroscience (335 citations), Atomic and Molecular Physics, and Optics (562 citations) and Computer Networks and Communications (400 citations). David Cai has collaborated with scholars based in United States, China and United Arab Emirates. Frequent co-authors include Niels Grønbech‐Jensen, David W. McLaughlin, A. R. Bishop, Aaditya V. Rangan, Douglas Zhou, Dan Hu, Gregor Kovačič, Andrew J. Majda, Louis Tao and Esteban G. Tabak. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Computational Neuroscience, Physical Review Letters, Physical review. B, Condensed matter and Physical review. E.

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.

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