Muhammad Awais
- Artificial Intelligence top 10%
- Health Information Management top 2%
- Computer Vision and Pattern Recognition top 10%
- Information Systems top 10%
- Control and Systems Engineering
- Co-authors
- Dominik HenrichMuhammad SherAnwar GhaniSyed Muhammad SaqlainMuhammad Usman AshrafFaiz Ali ShahImran KhanMuhammad Younas
- Topics
- Robot Manipulation and Learning (5 papers)Robotic Path Planning Algorithms (3 papers)Reinforcement Learning in Robotics (3 papers)
In The Last Decade
Muhammad Awais
18 papers receiving 359 citations
Peers
Comparison fields: 5 of 94
- Artificial Intelligence 159
- Health Information Management 69
- Computer Vision and Pattern Recognition 68
- Information Systems 52
- Control and Systems Engineering 49
Countries citing papers authored by Muhammad Awais
This map shows the geographic impact of Muhammad Awais'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 Awais with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Muhammad Awais more than expected).
Fields of papers citing papers by Muhammad Awais
This network shows the impact of papers produced by Muhammad Awais. 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 Awais. The network helps show where Muhammad Awais may publish in the future.
Co-authorship network of co-authors of Muhammad Awais
This figure shows the co-authorship network connecting the top 25 collaborators of Muhammad Awais. A scholar is included among the top collaborators of Muhammad Awais 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 Awais. Muhammad Awais is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 8 | |
| 2 | 63 | |
| 3 | 13 | |
| 4 | 32 | |
| 5 | 25 | |
| 6 | 16 | |
| 7 | Real-Time Vision-Based Localization of Planar Cable-Driven Parallel Robot | 2 |
| 8 | 3 | |
| 9 | 107 | |
| 10 | 2 | |
| 11 | Requirements Prioritization: Challenges and Techniques for Quality Software Development | 6 |
| 12 | Memory Management: Challenges and Techniques for traditional Memory Allocation Algorithms in Relation with Today's Real Time Needs | 3 |
| 13 | 1 | |
| 14 | 22 | |
| 15 | Helpful Business Value of Advance Bal Information System | 5 |
| 16 | 19 | |
| 17 | 44 | |
| 18 | IMPROVED LASER-BASED NAVIGATION FOR MOBILE ROBOTS | 5 |
About Muhammad Awais
Muhammad Awais is a scholar working on Control and Systems Engineering, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 18 papers that have together received 376 indexed citations. Recurring topics across this work include Robot Manipulation and Learning (5 papers), Robotic Path Planning Algorithms (3 papers) and Reinforcement Learning in Robotics (3 papers). The work is most often cited by research in Health Information Management (69 citations), Artificial Intelligence (159 citations) and Medical Laboratory Technology (6 citations). Muhammad Awais has collaborated with scholars based in Pakistan, Germany and Malaysia. Frequent co-authors include Dominik Henrich, Muhammad Sher, Anwar Ghani, Syed Muhammad Saqlain, Muhammad Usman Ashraf, Faiz Ali Shah, Imran Khan, Muhammad Younas, Muhammad Sheraz Arshad Malik and Ramzan Talib. Their work appears in journals such as IEEE Access, International Journal of Biological Macromolecules and Current Science.
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.