Kayvon Daie

33 total papers · 2.4k total citations
15 papers, 1.3k citations indexed

About

Kayvon Daie is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Electrical and Electronic Engineering. According to data from OpenAlex, Kayvon Daie has authored 15 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Cognitive Neuroscience, 10 papers in Cellular and Molecular Neuroscience and 3 papers in Electrical and Electronic Engineering. Recurrent topics in Kayvon Daie's work include Neural dynamics and brain function (11 papers), Neuroscience and Neuropharmacology Research (5 papers) and EEG and Brain-Computer Interfaces (3 papers). Kayvon Daie is often cited by papers focused on Neural dynamics and brain function (11 papers), Neuroscience and Neuropharmacology Research (5 papers) and EEG and Brain-Computer Interfaces (3 papers). Kayvon Daie collaborates with scholars based in United States, Taiwan and Israel. Kayvon Daie's co-authors include Karel Svoboda, Shaul Druckmann, Nuo Li, H. Inagaki, Charles R. Gerfen, Zengcai V. Guo, Emre Aksay, Tsai‐Wen Chen, David W. Tank and Andrew Miri and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Neuron.

In The Last Decade

Kayvon Daie

14 papers receiving 1.3k citations

Hit Papers

Maintenance of persistent... 2017 2026 2020 2023 2017 100 200 300

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Kayvon Daie 934 634 172 153 147 15 1.3k
J. van Pelt 858 0.9× 1.0k 1.6× 221 1.3× 73 0.5× 167 1.1× 42 1.5k
Jason N. MacLean 1.1k 1.2× 986 1.6× 213 1.2× 211 1.4× 146 1.0× 47 1.6k
Jeffrey E. Markowitz 566 0.6× 579 0.9× 123 0.7× 115 0.8× 112 0.8× 21 1.1k
Simon Peron 1.3k 1.4× 1.2k 1.9× 215 1.3× 62 0.4× 138 0.9× 17 1.7k
Roland Dürr 568 0.6× 559 0.9× 300 1.7× 67 0.4× 56 0.4× 21 1.2k
Cora Sau Wan Lai 682 0.7× 729 1.1× 319 1.9× 79 0.5× 110 0.7× 33 1.6k
Sue Ann Koay 744 0.8× 610 1.0× 210 1.2× 69 0.5× 52 0.4× 13 1.2k
Andrew J. Peters 1.1k 1.2× 723 1.1× 146 0.8× 59 0.4× 45 0.3× 18 1.5k
Ashley Juavinett 997 1.1× 671 1.1× 191 1.1× 51 0.3× 57 0.4× 21 1.3k
Ning-long Xu 1.1k 1.2× 980 1.5× 180 1.0× 36 0.2× 119 0.8× 22 1.4k

Countries citing papers authored by Kayvon Daie

Since Specialization
Citations

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

Fields of papers citing papers by Kayvon Daie

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kayvon Daie

This figure shows the co-authorship network connecting the top 25 collaborators of Kayvon Daie. A scholar is included among the top collaborators of Kayvon Daie 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 Kayvon Daie. Kayvon Daie is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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