Monika Mangla
- Artificial Intelligence top 10%
- Management Science and Operations Research top 10%
- Computer Networks and Communications top 10%
- Electrical and Electronic Engineering
- Information Systems top 10%
- Co-authors
- Nonita SharmaSachi Nandan MohantyShitharth SelvarajanSuneeta SatpathyMajdi RawashdehDeepak GuptaMohammad ShorfuzzamanPrayag Tiwari
- Topics
- COVID-19 epidemiological studies (5 papers)Artificial Intelligence in Healthcare (4 papers)Blockchain Technology Applications and Security (4 papers)
- Journals
- SHILAP Revista de lepidopterologíaKnowledge-Based SystemsBiomedical Signal Processing and Control
- Partner nations
- IndiaUnited StatesMalaysia
In The Last Decade
Monika Mangla
43 papers receiving 370 citations
Peers
Comparison fields: 5 of 106
- Artificial Intelligence 127
- Management Science and Operations Research 81
- Computer Networks and Communications 70
- Electrical and Electronic Engineering 58
- Information Systems 54
Countries citing papers authored by Monika Mangla
This map shows the geographic impact of Monika Mangla'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 Monika Mangla with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Monika Mangla more than expected).
Fields of papers citing papers by Monika Mangla
This network shows the impact of papers produced by Monika Mangla. 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 Monika Mangla. The network helps show where Monika Mangla may publish in the future.
Co-authorship network of co-authors of Monika Mangla
This figure shows the co-authorship network connecting the top 25 collaborators of Monika Mangla. A scholar is included among the top collaborators of Monika Mangla 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 Monika Mangla. Monika Mangla 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 | 0 | |
| 3 | 0 | |
| 4 | 5 | |
| 5 | 1 | |
| 6 | 4 | |
| 7 | 5 | |
| 8 | 0 | |
| 9 | 0 | |
| 10 | 0 | |
| 11 | 0 | |
| 12 | 42 | |
| 13 | 69 | |
| 14 | 22 | |
| 15 | Blockchain and IPFS Based Framework for Secure Student Document Record Keeping | 2 |
| 16 | 1 | |
| 17 | 6 | |
| 18 | 32 | |
| 19 | 5 | |
| 20 | 2 |
About Monika Mangla
Monika Mangla is a scholar working on Modeling and Simulation, Health Information Management and Artificial Intelligence, having authored 55 papers that have together received 393 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (5 papers), Artificial Intelligence in Healthcare (4 papers) and Blockchain Technology Applications and Security (4 papers). The work is most often cited by research in Health Information Management (33 citations), Management Science and Operations Research (81 citations) and Health Informatics (7 citations). Monika Mangla has collaborated with scholars based in India, United States and Malaysia. Frequent co-authors include Nonita Sharma, Sachi Nandan Mohanty, Shitharth Selvarajan, Suneeta Satpathy, Majdi Rawashdeh, Deepak Gupta, Mohammad Shorfuzzaman, Prayag Tiwari, Nitin Goyal and Deepti Kakkar. Their work appears in journals such as SHILAP Revista de lepidopterología, Knowledge-Based Systems and Biomedical Signal Processing and Control.
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.