M. Suresha
Impact in
- General Social Sciences top 5%
- Artificial Intelligence top 10%
- Hate Speech and Cyberbullying Detection
- Advanced Text Analysis Techniques
- Sentiment Analysis and Opinion Mining
- Topic Modeling
Papers in
-
- Text and Document Classification Technologies 4
- Topic Modeling 3
-
- Cloud Computing and Resource Management 5
- Blockchain Technology Applications and Security 2
- Co-authors
- Mufeed Ahmed Naji Saif (3 shared papers)Jemal Abawajy (3 shared papers)Ajit Danti (2 shared papers)Aida A. Nasr (1 shared paper)
In The Last Decade
M. Suresha
21 papers receiving 285 citations
Peers
Comparison fields: 5 of 63
- General Social Sciences 21
- Artificial Intelligence 165
- Information Systems 102
- Signal Processing 39
- Computer Networks and Communications 70
Countries citing papers authored by M. Suresha
This map shows the geographic impact of M. Suresha'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 M. Suresha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. Suresha more than expected).
Fields of papers citing papers by M. Suresha
This network shows the impact of papers produced by M. Suresha. 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 M. Suresha. The network helps show where M. Suresha may publish in the future.
Co-authors
The 4 scholars most cited alongside M. Suresha, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 79 | |
| 2 | 2022 | 46 | |
| 3 | 2022 | 21 | |
| 4 | 2018 | 21 | |
| 5 | 2020 | 19 | |
| 6 | 2019 | 15 | |
| 7 | 2021 | 11 | |
| 8 | 2019 | 10 | |
| 9 | 2021 | 10 | |
| 10 | 2017 | 9 | |
| 11 | 2013 | 9 | |
| 12 | 2018 | 8 | |
| 13 | 2019 | 7 | |
| 14 | 2017 | 6 | |
| 15 | 2012 | 6 | |
| 16 | 2012 | 6 | |
| 17 | 2019 | 6 | |
| 18 | 2019 | 4 | |
| 19 | 2018 | 4 | |
| 20 | 2017 | 2 |
About M. Suresha
M. Suresha is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Computer Networks and Communications and Signal Processing, having authored 22 papers that have together received 301 indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (5 papers), Cloud Computing and Resource Management (5 papers), Text and Document Classification Technologies (4 papers), Spectroscopy and Chemometric Analyses (3 papers), Topic Modeling (3 papers), Distributed and Parallel Computing Systems (3 papers), Blockchain Technology Applications and Security (2 papers) and Face and Expression Recognition (2 papers). The work is most often cited by research in General Social Sciences (21 citations), Artificial Intelligence (165 citations), Information Systems (102 citations), Signal Processing (39 citations) and Computer Networks and Communications (70 citations). M. Suresha has collaborated with scholars based in India, Yemen and Australia. Frequent co-authors include Mufeed Ahmed Naji Saif, Jemal Abawajy, Ajit Danti and Aida A. Nasr. Their work appears in journals such as IEEE Access, Artificial Intelligence Review, Expert Systems with Applications, International Journal of High Performance Computing and Networking and Cluster Computing.
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.