M. Atif Qureshi
- Artificial Intelligence
- Clinical Psychology
- Information Systems
- Marketing
- Statistical and Nonlinear Physics
- Co-authors
- Derek GreeneAwais ManzoorMuhammad Zahid LatifLuca LongoLuis Miralles‐PechuánThien Huynh‐TheThippa Reddy GadekalluGabriella Pasi
- Topics
- Topic Modeling (9 papers)Advanced Text Analysis Techniques (5 papers)Wikis in Education and Collaboration (4 papers)
In The Last Decade
M. Atif Qureshi
31 papers receiving 218 citations
Peers
Comparison fields: 5 of 83
- Artificial Intelligence 77
- Clinical Psychology 40
- Information Systems 32
- Marketing 25
- Statistical and Nonlinear Physics 24
Countries citing papers authored by M. Atif Qureshi
This map shows the geographic impact of M. Atif Qureshi'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. Atif Qureshi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. Atif Qureshi more than expected).
Fields of papers citing papers by M. Atif Qureshi
This network shows the impact of papers produced by M. Atif Qureshi. 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. Atif Qureshi. The network helps show where M. Atif Qureshi may publish in the future.
Co-authorship network of co-authors of M. Atif Qureshi
This figure shows the co-authorship network connecting the top 25 collaborators of M. Atif Qureshi. A scholar is included among the top collaborators of M. Atif Qureshi 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 M. Atif Qureshi. M. Atif Qureshi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 43 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 3 | |
| 9 | 1 | |
| 10 | 1 | |
| 11 | 19 | |
| 12 | CIRGIRGDISCO at RepLab2014 Reputation Dimension Task: Using Wikipedia Graph Structure for Classifying the Reputation Dimension of a Tweet. | 0 |
| 13 | Exploiting wikipedia to identify domain-specific key terms/phrases from a short-text collection | 2 |
| 14 | YummyKarachi: Using Real-Time Tweets for Restaurant Recommendations in an Unsafe Location | 1 |
| 15 | Concept Term Expansion Approach for Monitoring Reputation of Companies on Twitter | 3 |
| 16 | 0 | |
| 17 | 8 | |
| 18 | Improving the Quality of Web Spam Filtering by Using Seed Refinement | 0 |
| 19 | Comparative Study of VoIP over WiMax and WiFi | 9 |
| 20 | Identifying and Ranking Topic Clusters in the Blogosphere | 4 |
About M. Atif Qureshi
M. Atif Qureshi is a scholar working on Health Informatics, Communication and Medical Laboratory Technology, having authored 40 papers that have together received 240 indexed citations. Recurring topics across this work include Topic Modeling (9 papers), Advanced Text Analysis Techniques (5 papers) and Wikis in Education and Collaboration (4 papers). The work is most often cited by research in Communication (19 citations), Marketing (25 citations) and Applied Microbiology and Biotechnology (5 citations). M. Atif Qureshi has collaborated with scholars based in Ireland, Pakistan and Italy. Frequent co-authors include Derek Greene, Awais Manzoor, Muhammad Zahid Latif, Luca Longo, Luis Miralles‐Pechuán, Thien Huynh‐The, Thippa Reddy Gadekallu, Gabriella Pasi, Colm O’Riordan and Shen Wang. Their work appears in journals such as IEEE Access, Genes and Journal of Ambient Intelligence and Humanized 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.