Nishith Reddy Mannuru
- Artificial Intelligence top 5%
- Health Informatics top 0.2%
- Computer Science Applications top 2%
- Safety Research top 5%
- Information Systems top 10%
- Co-authors
- Brady LundTing WangSomipam R. ShimrayZoë Abbie TeelAgostino MarengoJenny PangeAlessandro PaganoSakib Shahriar
- Topics
- Artificial Intelligence in Healthcare and Education (11 papers)Topic Modeling (6 papers)COVID-19 diagnosis using AI (5 papers)
- Journals
- SHILAP Revista de lepidopterologíaApplied SciencesJournal of Health Communication
- Partner nations
- United StatesIndiaIran
In The Last Decade
Nishith Reddy Mannuru
18 papers receiving 797 citations
Hit Papers
Peers
Comparison fields: 5 of 105
- Artificial Intelligence 376
- Health Informatics 359
- Computer Science Applications 176
- Safety Research 141
- Information Systems 95
Countries citing papers authored by Nishith Reddy Mannuru
This map shows the geographic impact of Nishith Reddy Mannuru'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 Nishith Reddy Mannuru with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nishith Reddy Mannuru more than expected).
Fields of papers citing papers by Nishith Reddy Mannuru
This network shows the impact of papers produced by Nishith Reddy Mannuru. 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 Nishith Reddy Mannuru. The network helps show where Nishith Reddy Mannuru may publish in the future.
Co-authorship network of co-authors of Nishith Reddy Mannuru
This figure shows the co-authorship network connecting the top 25 collaborators of Nishith Reddy Mannuru. A scholar is included among the top collaborators of Nishith Reddy Mannuru 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 Nishith Reddy Mannuru. Nishith Reddy Mannuru is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 5 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 6 | |
| 6 | 0 | |
| 7 | 0 | |
| 8 | 4 | |
| 9 | 4 | |
| 10 | 2 | |
| 11 | 0 | |
| 12 | 1 | |
| 13 | 13 | |
| 14 | 7 | |
| 15 | 156 | |
| 16 | 3 | |
| 17 | 450 | |
| 18 | 21 | |
| 19 | 141 | |
| 20 | 4 |
About Nishith Reddy Mannuru
Nishith Reddy Mannuru is a scholar working on Health Informatics, Safety Research and Computer Science Applications, having authored 23 papers that have together received 863 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare and Education (11 papers), Topic Modeling (6 papers) and COVID-19 diagnosis using AI (5 papers). The work is most often cited by research in Health Informatics (359 citations), Computer Science Applications (176 citations) and Safety Research (141 citations). Nishith Reddy Mannuru has collaborated with scholars based in United States, India and Iran. Frequent co-authors include Brady Lund, Ting Wang, Somipam R. Shimray, Zoë Abbie Teel, Agostino Marengo, Jenny Pange, Alessandro Pagano, Sakib Shahriar, Daniel Agbaji and Kadhim Hayawi. Their work appears in journals such as SHILAP Revista de lepidopterología, Applied Sciences and Journal of Health Communication.
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.