Kamal Ali
- Artificial Intelligence top 2%
- Information Systems top 2%
- Computer Vision and Pattern Recognition top 5%
- Computational Theory and Mathematics top 5%
- Signal Processing top 10%
- Co-authors
- Michael J. PazzaniStefanos ManganarisRamakrishnan SrikantAshok N. SrivastavaM. J. WayJeffrey D. ScargleR. K. Fakher AlfahedSteven P. Ketchpel
- Topics
- Machine Learning and Data Classification (7 papers)Imbalanced Data Classification Techniques (5 papers)Artificial Intelligence in Games (4 papers)
- Partner nations
- United StatesIraqAustralia
In The Last Decade
Kamal Ali
22 papers receiving 807 citations
Peers
Comparison fields: 5 of 116
- Artificial Intelligence 476
- Information Systems 336
- Computer Vision and Pattern Recognition 168
- Computational Theory and Mathematics 110
- Signal Processing 88
Countries citing papers authored by Kamal Ali
This map shows the geographic impact of Kamal Ali'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 Kamal Ali with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kamal Ali more than expected).
Fields of papers citing papers by Kamal Ali
This network shows the impact of papers produced by Kamal Ali. 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 Kamal Ali. The network helps show where Kamal Ali may publish in the future.
Co-authorship network of co-authors of Kamal Ali
This figure shows the co-authorship network connecting the top 25 collaborators of Kamal Ali. A scholar is included among the top collaborators of Kamal Ali 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 Kamal Ali. Kamal Ali is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 17 | |
| 3 | 7 | |
| 4 | 47 | |
| 5 | 16 | |
| 6 | Improving Structural Knowledge Transfer with Parametric Adaptation | 1 |
| 7 | Learning Hierarchical Skills for Game Agents from Video of Human Behavior | 1 |
| 8 | 9 | |
| 9 | 15 | |
| 10 | 137 | |
| 11 | 5 | |
| 12 | Partial classification using association rules | 133 |
| 13 | Learning probabilistic relational concept descriptions | 9 |
| 14 | 124 | |
| 15 | 6 | |
| 16 | On the link between error correlation and error reduction in decision tree ensembles | 43 |
| 17 | Trading off coverage for accuracy in forecasts: Applications to clinical data analysis | 7 |
| 18 | 170 | |
| 19 | HYDRA: A Noise-tolerant Relational Concept Learning Algorithm. | 27 |
| 20 | 4 |
About Kamal Ali
Kamal Ali is a scholar working on Artificial Intelligence, Information Systems and Radiological and Ultrasound Technology, having authored 22 papers that have together received 877 indexed citations. Recurring topics across this work include Machine Learning and Data Classification (7 papers), Imbalanced Data Classification Techniques (5 papers) and Artificial Intelligence in Games (4 papers). The work is most often cited by research in Information Systems (336 citations), Artificial Intelligence (476 citations) and Computer Vision and Pattern Recognition (168 citations). Kamal Ali has collaborated with scholars based in United States, Iraq and Australia. Frequent co-authors include Michael J. Pazzani, Stefanos Manganaris, Ramakrishnan Srikant, Ashok N. Srivastava, M. J. Way, Jeffrey D. Scargle, R. K. Fakher Alfahed, Steven P. Ketchpel, Dan Shapiro and Burak Kadem. Their work appears in journals such as Machine Learning, Knowledge-Based Systems and AI Magazine.
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.