Muhammad Azeem Abbas
- Information Systems top 10%
- Artificial Intelligence
- Computer Science Applications top 5%
- Education
- Computer Vision and Pattern Recognition
- Co-authors
- Sharifullah KhanYaser HafeezAsif NawazGwo‐Jen HwangBushra HamidMuhammad Taha JilaniArshia RehmanMuhammad Aqib
- Topics
- Mobile Learning in Education (4 papers)Intelligent Tutoring Systems and Adaptive Learning (4 papers)Online Learning and Analytics (3 papers)
- Partner nations
- PakistanUnited KingdomMalaysia
In The Last Decade
Muhammad Azeem Abbas
35 papers receiving 264 citations
Peers
Comparison fields: 5 of 80
- Information Systems 94
- Artificial Intelligence 83
- Computer Science Applications 73
- Education 47
- Computer Vision and Pattern Recognition 28
Countries citing papers authored by Muhammad Azeem Abbas
This map shows the geographic impact of Muhammad Azeem Abbas'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 Muhammad Azeem Abbas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Muhammad Azeem Abbas more than expected).
Fields of papers citing papers by Muhammad Azeem Abbas
This network shows the impact of papers produced by Muhammad Azeem Abbas. 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 Muhammad Azeem Abbas. The network helps show where Muhammad Azeem Abbas may publish in the future.
Co-authorship network of co-authors of Muhammad Azeem Abbas
This figure shows the co-authorship network connecting the top 25 collaborators of Muhammad Azeem Abbas. A scholar is included among the top collaborators of Muhammad Azeem Abbas 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 Muhammad Azeem Abbas. Muhammad Azeem Abbas 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 | 2 | |
| 3 | 6 | |
| 4 | 4 | |
| 5 | 23 | |
| 6 | 2 | |
| 7 | 8 | |
| 8 | An Empirical Throughput Analysis of Multimedia Applications with OpenFlow-based Dynamic Load Balancing Approach in WLAN | 1 |
| 9 | Determining Influential Factors and Challenges in Automatic Taxonomy Generation: A Systematic Literature Review of Techniques 1999-2016. | 1 |
| 10 | 4 | |
| 11 | 1 | |
| 12 | Enabling profound hearing impaired children to articulate words using lip-reading through software application. | 1 |
| 13 | 25 | |
| 14 | 1 | |
| 15 | 42 | |
| 16 | 2 | |
| 17 | 5 | |
| 18 | 2 | |
| 19 | 3 | |
| 20 | 3 |
About Muhammad Azeem Abbas
Muhammad Azeem Abbas is a scholar working on Computer Science Applications, Information Systems and Artificial Intelligence, having authored 37 papers that have together received 278 indexed citations. Recurring topics across this work include Mobile Learning in Education (4 papers), Intelligent Tutoring Systems and Adaptive Learning (4 papers) and Online Learning and Analytics (3 papers). The work is most often cited by research in Computer Science Applications (73 citations), Health Informatics (6 citations) and Information Systems (94 citations). Muhammad Azeem Abbas has collaborated with scholars based in Pakistan, United Kingdom and Malaysia. Frequent co-authors include Sharifullah Khan, Yaser Hafeez, Asif Nawaz, Gwo‐Jen Hwang, Bushra Hamid, Muhammad Taha Jilani, Arshia Rehman, Muhammad Aqib, Sadia Ali and Saheed Ajayi. Their work appears in journals such as PLoS ONE, British Journal of Educational Technology and Multimedia Tools and Applications.
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.