Abdul Rauf Baig
- Artificial Intelligence top 5%
- Information Systems top 5%
- Computer Vision and Pattern Recognition top 10%
- Computational Theory and Mathematics top 5%
- Computer Networks and Communications top 10%
- Co-authors
- Hajira JabeenZahid HalimAyesha KhanKashif ZafarWaseem ShahzadMuhammad RashidZunera JalilShakir Khan
- Topics
- Metaheuristic Optimization Algorithms Research (22 papers)Evolutionary Algorithms and Applications (21 papers)Advanced Multi-Objective Optimization Algorithms (11 papers)
- Cited by
- Artificial IntelligenceComputational Theory and MathematicsComputer Vision and Pattern Recognition
- Partner nations
- PakistanSaudi ArabiaBangladesh
In The Last Decade
Abdul Rauf Baig
74 papers receiving 753 citations
Peers
Comparison fields: 5 of 114
- Artificial Intelligence 438
- Information Systems 145
- Computer Vision and Pattern Recognition 134
- Computational Theory and Mathematics 121
- Computer Networks and Communications 95
Countries citing papers authored by Abdul Rauf Baig
This map shows the geographic impact of Abdul Rauf Baig'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 Abdul Rauf Baig with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Abdul Rauf Baig more than expected).
Fields of papers citing papers by Abdul Rauf Baig
This network shows the impact of papers produced by Abdul Rauf Baig. 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 Abdul Rauf Baig. The network helps show where Abdul Rauf Baig may publish in the future.
Co-authorship network of co-authors of Abdul Rauf Baig
This figure shows the co-authorship network connecting the top 25 collaborators of Abdul Rauf Baig. A scholar is included among the top collaborators of Abdul Rauf Baig 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 Abdul Rauf Baig. Abdul Rauf Baig is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 9 | |
| 2 | 7 | |
| 3 | 23 | |
| 4 | 22 | |
| 5 | 47 | |
| 6 | 3 | |
| 7 | 22 | |
| 8 | 2 | |
| 9 | 9 | |
| 10 | 1 | |
| 11 | 0 | |
| 12 | 19 | |
| 13 | 5 | |
| 14 | 6 | |
| 15 | 5 | |
| 16 | 0 | |
| 17 | 14 | |
| 18 | 1 | |
| 19 | Spatial-Temporal artificial neurons applied to online cursive handwritten recognition. | 1 |
| 20 | A Fully-Neural Solution for on-Line Handwritten Character Recognition | 4 |
About Abdul Rauf Baig
Abdul Rauf Baig is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Computer Vision and Pattern Recognition, having authored 78 papers that have together received 792 indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (22 papers), Evolutionary Algorithms and Applications (21 papers) and Advanced Multi-Objective Optimization Algorithms (11 papers). The work is most often cited by research in Artificial Intelligence (438 citations), Computational Theory and Mathematics (121 citations) and Computer Vision and Pattern Recognition (134 citations). Abdul Rauf Baig has collaborated with scholars based in Pakistan, Saudi Arabia and Bangladesh. Frequent co-authors include Hajira Jabeen, Zahid Halim, Ayesha Khan, Kashif Zafar, Waseem Shahzad, Muhammad Rashid, Zunera Jalil, Shakir Khan, Qaisar Abbas and Salabat Khan. Their work appears in journals such as Computers in Human Behavior, IEEE Access and Sensors.
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.