Wu Dai
About
In The Last Decade
Wu Dai
82 papers receiving 850 citations
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late) cites · hero ref
| Name | h | Career | Trend | Papers | Cites | |||||
|---|---|---|---|---|---|---|---|---|---|---|
| Wu Dai China | 17 | 508 | 479 | 364 | 312 | 185 | 89 | 886 | ||
| Jesus F. Esquivel United States | 17 | 224 0.4× | 535 1.1× | 404 1.1× | 176 0.6× | 122 0.7× | 55 | 725 | ||
| Dhana Raj Boina United States | 13 | 603 1.2× | 659 1.4× | 136 0.4× | 153 0.5× | 78 0.4× | 22 | 843 | ||
| Andy Michel United States | 17 | 315 0.6× | 483 1.0× | 113 0.3× | 355 1.1× | 89 0.5× | 28 | 746 | ||
| S. P. Foster New Zealand | 17 | 318 0.6× | 835 1.7× | 298 0.8× | 318 1.0× | 206 1.1× | 42 | 989 | ||
| Ya‐Jun Gong China | 18 | 365 0.7× | 689 1.4× | 227 0.6× | 431 1.4× | 298 1.6× | 42 | 956 | ||
| Wendy L. Meyer United States | 16 | 489 1.0× | 754 1.6× | 161 0.4× | 129 0.4× | 103 0.6× | 32 | 923 | ||
| Ken‐ichiro Honda Japan | 13 | 372 0.7× | 550 1.1× | 249 0.7× | 61 0.2× | 96 0.5× | 34 | 729 | ||
| Pierre Fouillet France | 20 | 134 0.3× | 759 1.6× | 288 0.8× | 75 0.2× | 233 1.3× | 25 | 961 | ||
| Anne Le Ralec France | 18 | 561 1.1× | 1.0k 2.1× | 636 1.7× | 128 0.4× | 165 0.9× | 41 | 1.2k | ||
| Eduardo Gonçalves Paterson Fox Brazil | 13 | 91 0.2× | 411 0.9× | 223 0.6× | 69 0.2× | 408 2.2× | 60 | 635 |
Countries citing papers authored by Wu Dai
This map shows the geographic impact of Wu 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 Wu Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wu Dai more than expected).
Fields of papers citing papers by Wu Dai
This network shows the impact of papers produced by Wu 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 Wu Dai. The network helps show where Wu Dai may publish in the future.
Co-authorship network of co-authors of Wu Dai
This figure shows the co-authorship network connecting the top 25 collaborators of Wu Dai. A scholar is included among the top collaborators of Wu 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 Wu Dai. Wu Dai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
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.