Khalil El Hindi
- Artificial Intelligence top 5%
- Information Systems top 5%
- Computer Networks and Communications top 10%
- Management Science and Operations Research top 10%
- Computational Theory and Mathematics top 10%
- Co-authors
- Fadl DahanAhmed GhoneimHussain AlSalmanMousa Al-AkhrasHassan MathkourAmel Ali AlhussanBayan Abu ShawarMona Jamjoom
- Topics
- Machine Learning and Data Classification (13 papers)Bayesian Modeling and Causal Inference (8 papers)Text and Document Classification Technologies (8 papers)
- Partner nations
- Saudi ArabiaJordanChina
In The Last Decade
Khalil El Hindi
34 papers receiving 452 citations
Peers
Comparison fields: 5 of 84
- Artificial Intelligence 273
- Information Systems 134
- Computer Networks and Communications 75
- Management Science and Operations Research 53
- Computational Theory and Mathematics 51
Countries citing papers authored by Khalil El Hindi
This map shows the geographic impact of Khalil El Hindi'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 Khalil El Hindi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Khalil El Hindi more than expected).
Fields of papers citing papers by Khalil El Hindi
This network shows the impact of papers produced by Khalil El Hindi. 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 Khalil El Hindi. The network helps show where Khalil El Hindi may publish in the future.
Co-authorship network of co-authors of Khalil El Hindi
This figure shows the co-authorship network connecting the top 25 collaborators of Khalil El Hindi. A scholar is included among the top collaborators of Khalil El Hindi 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 Khalil El Hindi. Khalil El Hindi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 3 | |
| 4 | 4 | |
| 5 | 1 | |
| 6 | 0 | |
| 7 | 2 | |
| 8 | 2 | |
| 9 | 0 | |
| 10 | 1 | |
| 11 | 4 | |
| 12 | 33 | |
| 13 | 25 | |
| 14 | 49 | |
| 15 | Combining instance weighting and fine tuning for training naïve bayesian classifiers with scanttrainingdata. | 3 |
| 16 | 16 | |
| 17 | 14 | |
| 18 | 2 | |
| 19 | Bayesian-based instance weighting techniques for instance-based learners | 0 |
| 20 | 0 |
About Khalil El Hindi
Khalil El Hindi is a scholar working on Artificial Intelligence, Information Systems and Computer Networks and Communications, having authored 42 papers that have together received 477 indexed citations. Recurring topics across this work include Machine Learning and Data Classification (13 papers), Bayesian Modeling and Causal Inference (8 papers) and Text and Document Classification Technologies (8 papers). The work is most often cited by research in Artificial Intelligence (273 citations), Information Systems (134 citations) and Management Science and Operations Research (53 citations). Khalil El Hindi has collaborated with scholars based in Saudi Arabia, Jordan and China. Frequent co-authors include Fadl Dahan, Ahmed Ghoneim, Hussain AlSalman, Mousa Al-Akhras, Hassan Mathkour, Amel Ali Alhussan, Bayan Abu Shawar, Mona Jamjoom, Saad Al-Ahmadi and Irfan‐Ullah Awan. Their work appears in journals such as IEEE Access, Sensors and Applied Soft 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.