Hailong Dao
About
In The Last Decade
Hailong Dao
44 papers receiving 340 citations
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late) cites · hero ref
| Name | h | Career | Trend | Papers | Cites | |||||
|---|---|---|---|---|---|---|---|---|---|---|
| Hailong Dao United States | 12 | 328 | 318 | 98 | 66 | 21 | 49 | 360 | ||
| Santiago Zarzuela Spain | 9 | 293 0.9× | 264 0.8× | 152 1.6× | 27 0.4× | 20 1.0× | 29 | 308 | ||
| Andrew R. Kustin United States | 15 | 480 1.5× | 436 1.4× | 230 2.3× | 60 0.9× | 41 2.0× | 51 | 518 | ||
| Giuseppe Pareschi Italy | 11 | 86 0.3× | 280 0.9× | 72 0.7× | 152 2.3× | 10 0.5× | 23 | 290 | ||
| Rodney Y. Sharp United Kingdom | 15 | 650 2.0× | 588 1.8× | 154 1.6× | 85 1.3× | 29 1.4× | 44 | 692 | ||
| Daniel Ferrand France | 7 | 234 0.7× | 234 0.7× | 60 0.6× | 63 1.0× | 24 1.1× | 9 | 314 | ||
| Gunnar Fløystad Norway | 8 | 180 0.5× | 207 0.7× | 85 0.9× | 54 0.8× | 43 2.0× | 35 | 237 | ||
| Marcel Moralès France | 9 | 200 0.6× | 161 0.5× | 165 1.7× | 13 0.2× | 18 0.9× | 35 | 221 | ||
| Graham Leuschke United States | 9 | 267 0.8× | 307 1.0× | 26 0.3× | 71 1.1× | 29 1.4× | 20 | 322 | ||
| Daniela La Mattina Italy | 15 | 432 1.3× | 430 1.4× | 122 1.2× | 47 0.7× | 29 1.4× | 36 | 433 | ||
| Yu. A. Bahturin Canada | 6 | 226 0.7× | 217 0.7× | 50 0.5× | 57 0.9× | 21 1.0× | 9 | 231 |
Countries citing papers authored by Hailong Dao
This map shows the geographic impact of Hailong Dao'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 Hailong Dao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hailong Dao more than expected).
Fields of papers citing papers by Hailong Dao
This network shows the impact of papers produced by Hailong Dao. 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 Hailong Dao. The network helps show where Hailong Dao may publish in the future.
Co-authorship network of co-authors of Hailong Dao
This figure shows the co-authorship network connecting the top 25 collaborators of Hailong Dao. A scholar is included among the top collaborators of Hailong Dao 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 Hailong Dao. Hailong Dao 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.