Prasha Shrestha
- Artificial Intelligence top 10%
- Information Systems top 10%
- Infectious Diseases
- Molecular Biology
- Sociology and Political Science
- Co-authors
- Thamar SolorioFabio A. GonzálezPaolo RossoManuel MontesKul RajSuraj MaharjanJi‐Long ChenYun Chen
- Topics
- Topic Modeling (6 papers)Natural Language Processing Techniques (5 papers)Mental Health via Writing (4 papers)
- Partner nations
- United StatesChinaMexico
In The Last Decade
Prasha Shrestha
18 papers receiving 279 citations
Peers
Comparison fields: 5 of 84
- Artificial Intelligence 153
- Information Systems 60
- Infectious Diseases 53
- Molecular Biology 30
- Sociology and Political Science 30
Countries citing papers authored by Prasha Shrestha
This map shows the geographic impact of Prasha Shrestha'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 Prasha Shrestha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Prasha Shrestha more than expected).
Fields of papers citing papers by Prasha Shrestha
This network shows the impact of papers produced by Prasha Shrestha. 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 Prasha Shrestha. The network helps show where Prasha Shrestha may publish in the future.
Co-authorship network of co-authors of Prasha Shrestha
This figure shows the co-authorship network connecting the top 25 collaborators of Prasha Shrestha. A scholar is included among the top collaborators of Prasha Shrestha 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 Prasha Shrestha. Prasha Shrestha is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 19 | |
| 3 | 55 | |
| 4 | 11 | |
| 5 | 24 | |
| 6 | 8 | |
| 7 | 10 | |
| 8 | 6 | |
| 9 | 8 | |
| 10 | 1 | |
| 11 | 102 | |
| 12 | Age and Gender Prediction on Health Forum Data | 4 |
| 13 | 5 | |
| 14 | 13 | |
| 15 | 1 | |
| 16 | 10 | |
| 17 | Machine Translation Evaluation Metric for Text Alignment. | 4 |
| 18 | A Simple Approach to Author Profiling in MapReduce. | 9 |
| 19 | Using a Variety of n-Grams for the Detection of Different Kinds of Plagiarism Notebook for PAN at CLEF 2013. | 8 |
About Prasha Shrestha
Prasha Shrestha is a scholar working on Applied Microbiology and Biotechnology, Endocrinology and Artificial Intelligence, having authored 19 papers that have together received 298 indexed citations. Recurring topics across this work include Topic Modeling (6 papers), Natural Language Processing Techniques (5 papers) and Mental Health via Writing (4 papers). The work is most often cited by research in Artificial Intelligence (153 citations), Applied Microbiology and Biotechnology (6 citations) and Infectious Diseases (53 citations). Prasha Shrestha has collaborated with scholars based in United States, China and Mexico. Frequent co-authors include Thamar Solorio, Fabio A. González, Paolo Rosso, Manuel Montes, Kul Raj, Suraj Maharjan, Ji‐Long Chen, Yun Chen, Shasha Liu and Mohamed Maarouf. Their work appears in journals such as PLoS ONE, Frontiers in Microbiology and Viruses.
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.