Jing Dai

34 total papers · 590 total citations
18 papers, 396 citations indexed

About

Jing Dai is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Experimental and Cognitive Psychology. According to data from OpenAlex, Jing Dai has authored 18 papers receiving a total of 396 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Cognitive Neuroscience, 4 papers in Cellular and Molecular Neuroscience and 4 papers in Experimental and Cognitive Psychology. Recurrent topics in Jing Dai's work include Functional Brain Connectivity Studies (6 papers), Mental Health Research Topics (4 papers) and Neural dynamics and brain function (3 papers). Jing Dai is often cited by papers focused on Functional Brain Connectivity Studies (6 papers), Mental Health Research Topics (4 papers) and Neural dynamics and brain function (3 papers). Jing Dai collaborates with scholars based in China, United States and United Kingdom. Jing Dai's co-authors include Su Lui, Wenjing Zhang, Siyi Li, Tao Bo, Na Hu, Youguo Tan, Qiyong Gong, Manxi He, Song Wang and Xueling Suo and has published in prestigious journals such as Nano Letters, ACS Nano and Brain Research.

In The Last Decade

Jing Dai

18 papers receiving 395 citations

Author Peers

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

Author Last Decade Papers Cites
Jing Dai 265 122 87 86 46 18 396
Anca‐Larisa Sandu 199 0.8× 124 1.0× 49 0.6× 72 0.8× 31 0.7× 24 431
Juliette Tobias‐Webb 143 0.5× 93 0.8× 41 0.5× 109 1.3× 39 0.8× 11 387
Jenna Reinen 224 0.8× 56 0.5× 82 0.9× 66 0.8× 22 0.5× 20 407
Luigi A. Maglanoc 219 0.8× 65 0.5× 153 1.8× 49 0.6× 37 0.8× 13 413
Max de Leeuw 204 0.8× 67 0.5× 66 0.8× 134 1.6× 23 0.5× 24 372
Stephanie Hare 249 0.9× 87 0.7× 69 0.8× 87 1.0× 41 0.9× 26 335
Youngwoo Bryan Yoon 233 0.9× 72 0.6× 72 0.8× 136 1.6× 73 1.6× 19 407
L. Morra 125 0.5× 48 0.4× 76 0.9× 186 2.2× 16 0.3× 13 412
Navona Calarco 253 1.0× 123 1.0× 60 0.7× 110 1.3× 17 0.4× 20 374
Jayachandra M. Raghava 180 0.7× 145 1.2× 38 0.4× 209 2.4× 26 0.6× 25 388

Countries citing papers authored by Jing Dai

Since Specialization
Citations

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

Fields of papers citing papers by Jing Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jing Dai

This figure shows the co-authorship network connecting the top 25 collaborators of Jing Dai. A scholar is included among the top collaborators of Jing Dai 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 Jing Dai. Jing Dai 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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