Saima Anwar Lashari
- Artificial Intelligence top 10%
- Computer Networks and Communications top 10%
- Computer Vision and Pattern Recognition top 10%
- Electrical and Electronic Engineering
- Information Systems top 10%
- Co-authors
- Rosziati IbrahimMohammad Khalid Imam RahmaniNorhalina SenanSurbhi BhatiaMurtaja Ali SaareSandeep SharmaSalil BharanyMohammed Shuaib
- Topics
- Neural Networks and Applications (6 papers)IoT and Edge/Fog Computing (5 papers)Vehicular Ad Hoc Networks (VANETs) (5 papers)
- Journals
- SHILAP Revista de lepidopterologíaIEEE AccessSustainability
- Partner nations
- MalaysiaSaudi ArabiaPakistan
In The Last Decade
Saima Anwar Lashari
37 papers receiving 373 citations
Peers
Comparison fields: 5 of 83
- Artificial Intelligence 135
- Computer Networks and Communications 108
- Computer Vision and Pattern Recognition 76
- Electrical and Electronic Engineering 70
- Information Systems 66
Countries citing papers authored by Saima Anwar Lashari
This map shows the geographic impact of Saima Anwar Lashari'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 Saima Anwar Lashari with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Saima Anwar Lashari more than expected).
Fields of papers citing papers by Saima Anwar Lashari
This network shows the impact of papers produced by Saima Anwar Lashari. 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 Saima Anwar Lashari. The network helps show where Saima Anwar Lashari may publish in the future.
Co-authorship network of co-authors of Saima Anwar Lashari
This figure shows the co-authorship network connecting the top 25 collaborators of Saima Anwar Lashari. A scholar is included among the top collaborators of Saima Anwar Lashari 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 Saima Anwar Lashari. Saima Anwar Lashari 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 | 10 | |
| 3 | 1 | |
| 4 | 4 | |
| 5 | 4 | |
| 6 | 8 | |
| 7 | 1 | |
| 8 | 33 | |
| 9 | 7 | |
| 10 | 1 | |
| 11 | 4 | |
| 12 | 57 | |
| 13 | 6 | |
| 14 | 11 | |
| 15 | 30 | |
| 16 | 5 | |
| 17 | 27 | |
| 18 | 6 | |
| 19 | Medical data classification using similarity measure of fuzzy soft set based distance measure | 8 |
| 20 | 0 |
About Saima Anwar Lashari
Saima Anwar Lashari is a scholar working on Health Information Management, Computer Vision and Pattern Recognition and Management Science and Operations Research, having authored 42 papers that have together received 407 indexed citations. Recurring topics across this work include Neural Networks and Applications (6 papers), IoT and Edge/Fog Computing (5 papers) and Vehicular Ad Hoc Networks (VANETs) (5 papers). The work is most often cited by research in Health Information Management (40 citations), Computer Networks and Communications (108 citations) and Artificial Intelligence (135 citations). Saima Anwar Lashari has collaborated with scholars based in Malaysia, Saudi Arabia and Pakistan. Frequent co-authors include Rosziati Ibrahim, Mohammad Khalid Imam Rahmani, Norhalina Senan, Surbhi Bhatia, Murtaja Ali Saare, Sandeep Sharma, Salil Bharany, Mohammed Shuaib, Deepika Koundal and Navneet Kaur. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Access and Sustainability.
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.