Mahsa Kaviani
About
In The Last Decade
Mahsa Kaviani
8 papers receiving 252 citations
Hit Papers
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late) cites · hero ref
| Name | h | Career | Trend | Papers | Cites | |||||
|---|---|---|---|---|---|---|---|---|---|---|
| Mahsa Kaviani United States | 5 | 159 | 158 | 130 | 45 | 39 | 11 | 259 | ||
| Hosein Maleki United States | 5 | 159 1.0× | 158 1.0× | 130 1.0× | 45 1.0× | 39 1.0× | 11 | 259 | ||
| Juliana Salomão United States | 8 | 134 0.8× | 82 0.5× | 113 0.9× | 46 1.0× | 58 1.5× | 14 | 229 | ||
| Keith H. Black United States | 7 | 146 0.9× | 122 0.8× | 78 0.6× | 39 0.9× | 22 0.6× | 50 | 225 | ||
| José L. Fillat United States | 7 | 127 0.8× | 157 1.0× | 118 0.9× | 34 0.8× | 84 2.2× | 19 | 234 | ||
| Zhiyao Chen United States | 8 | 183 1.2× | 146 0.9× | 159 1.2× | 52 1.2× | 24 0.6× | 15 | 291 | ||
| Nathan Foley-Fisher United States | 7 | 149 0.9× | 110 0.7× | 68 0.5× | 30 0.7× | 50 1.3× | 32 | 225 | ||
| Adam L. Aiken United States | 8 | 231 1.5× | 110 0.7× | 156 1.2× | 40 0.9× | 16 0.4× | 17 | 261 | ||
| Viktors Stebunovs United States | 11 | 242 1.5× | 158 1.0× | 101 0.8× | 19 0.4× | 102 2.6× | 37 | 311 | ||
| Yee Cheng Loon United States | 5 | 246 1.5× | 104 0.7× | 93 0.7× | 18 0.4× | 25 0.6× | 9 | 278 | ||
| Kleopatra Nikolaou Germany | 8 | 256 1.6× | 172 1.1× | 153 1.2× | 19 0.4× | 72 1.8× | 15 | 332 |
Countries citing papers authored by Mahsa Kaviani
This map shows the geographic impact of Mahsa Kaviani'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 Mahsa Kaviani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mahsa Kaviani more than expected).
Fields of papers citing papers by Mahsa Kaviani
This network shows the impact of papers produced by Mahsa Kaviani. 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 Mahsa Kaviani. The network helps show where Mahsa Kaviani may publish in the future.
Co-authorship network of co-authors of Mahsa Kaviani
This figure shows the co-authorship network connecting the top 25 collaborators of Mahsa Kaviani. A scholar is included among the top collaborators of Mahsa Kaviani 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 Mahsa Kaviani. Mahsa Kaviani 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.