Subigya Nepal

65 total papers · 1.6k total citations
31 papers, 854 citations indexed

About

Subigya Nepal is a scholar working on Experimental and Cognitive Psychology, Applied Psychology and Clinical Psychology. According to data from OpenAlex, Subigya Nepal has authored 31 papers receiving a total of 854 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Experimental and Cognitive Psychology, 15 papers in Applied Psychology and 8 papers in Clinical Psychology. Recurrent topics in Subigya Nepal's work include Mental Health Research Topics (17 papers), Digital Mental Health Interventions (15 papers) and COVID-19 and Mental Health (5 papers). Subigya Nepal is often cited by papers focused on Mental Health Research Topics (17 papers), Digital Mental Health Interventions (15 papers) and COVID-19 and Mental Health (5 papers). Subigya Nepal collaborates with scholars based in United States, United Kingdom and Israel. Subigya Nepal's co-authors include Andrew T. Campbell, Weichen Wang, Jeremy F. Huckins, Meghan L. Meyer, Alex W DaSilva, Courtney Rogers, Elin Hedlund, Eilis I Murphy, Dylan D. Wagner and Paul E. Holtzheimer and has published in prestigious journals such as Biological Psychiatry, Journal of Affective Disorders and Schizophrenia Bulletin.

In The Last Decade

Subigya Nepal

30 papers receiving 843 citations

Hit Papers

Mental Health and Behavio... 2020 2026 2022 2024 2020 100 200 300 400 500

Author Peers

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

Author Last Decade Papers Cites
Subigya Nepal 499 240 218 203 152 31 854
Courtney Rogers 649 1.3× 241 1.0× 192 0.9× 223 1.1× 152 1.0× 20 980
Alex W DaSilva 504 1.0× 324 1.4× 316 1.4× 231 1.1× 168 1.1× 12 944
Elin Hedlund 506 1.0× 174 0.7× 158 0.7× 181 0.9× 145 1.0× 13 717
Jialing Wu 480 1.0× 180 0.8× 118 0.5× 180 0.9× 148 1.0× 22 832
Merylin Monaro 478 1.0× 168 0.7× 132 0.6× 295 1.5× 87 0.6× 54 1.0k
Sai-fu Fung 299 0.6× 96 0.4× 151 0.7× 282 1.4× 119 0.8× 35 932
Xin Liu 409 0.8× 225 0.9× 69 0.3× 156 0.8× 132 0.9× 42 989
Lea Mascarell-Maricic 493 1.0× 109 0.5× 96 0.4× 182 0.9× 102 0.7× 14 755
Anastassiya Kovaleva 214 0.4× 121 0.5× 104 0.5× 197 1.0× 87 0.6× 36 713
Ernestina Etchemendy 479 1.0× 157 0.7× 225 1.0× 244 1.2× 110 0.7× 34 921

Countries citing papers authored by Subigya Nepal

Since Specialization
Citations

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

Fields of papers citing papers by Subigya Nepal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Subigya Nepal

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