Ahmed El-Kishky
- Artificial Intelligence top 5%
- Information Systems top 5%
- Computer Vision and Pattern Recognition top 10%
- Statistical and Nonlinear Physics top 10%
- Molecular Biology
- Co-authors
- Jiawei HanChi WangClare R. VossXiang RenVishrav ChaudharyFangbo TaoFrancisco GuzmánPhilipp Koehn
- Topics
- Topic Modeling (22 papers)Natural Language Processing Techniques (19 papers)Advanced Graph Neural Networks (8 papers)
- Journals
- Journal of Machine Learning ResearchProceedings of the VLDB EndowmentMinerva Access (University of Melbourne)
- Partner nations
- United StatesIsraelUnited Kingdom
In The Last Decade
Ahmed El-Kishky
29 papers receiving 426 citations
Peers
Comparison fields: 5 of 59
- Artificial Intelligence 392
- Information Systems 109
- Computer Vision and Pattern Recognition 62
- Statistical and Nonlinear Physics 47
- Molecular Biology 38
Countries citing papers authored by Ahmed El-Kishky
This map shows the geographic impact of Ahmed El-Kishky'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 Ahmed El-Kishky with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ahmed El-Kishky more than expected).
Fields of papers citing papers by Ahmed El-Kishky
This network shows the impact of papers produced by Ahmed El-Kishky. 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 Ahmed El-Kishky. The network helps show where Ahmed El-Kishky may publish in the future.
Co-authorship network of co-authors of Ahmed El-Kishky
This figure shows the co-authorship network connecting the top 25 collaborators of Ahmed El-Kishky. A scholar is included among the top collaborators of Ahmed El-Kishky 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 Ahmed El-Kishky. Ahmed El-Kishky is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 30 | |
| 3 | Beyond English-Centric Multilingual Machine Translation | 11 |
| 4 | 14 | |
| 5 | 4 | |
| 6 | 12 | |
| 7 | 29 | |
| 8 | 4 | |
| 9 | 4 | |
| 10 | 2 | |
| 11 | 1 | |
| 12 | 3 | |
| 13 | 4 | |
| 14 | 8 | |
| 15 | 10 | |
| 16 | 54 | |
| 17 | 3 | |
| 18 | 126 | |
| 19 | 10 | |
| 20 | 12 |
About Ahmed El-Kishky
Ahmed El-Kishky is a scholar working on Artificial Intelligence, Information Systems and Statistical and Nonlinear Physics, having authored 29 papers that have together received 455 indexed citations. Recurring topics across this work include Topic Modeling (22 papers), Natural Language Processing Techniques (19 papers) and Advanced Graph Neural Networks (8 papers). The work is most often cited by research in Artificial Intelligence (392 citations), Information Systems (109 citations) and Medical Terminology (1 citation). Ahmed El-Kishky has collaborated with scholars based in United States, Israel and United Kingdom. Frequent co-authors include Jiawei Han, Chi Wang, Clare R. Voss, Xiang Ren, Vishrav Chaudhary, Fangbo Tao, Francisco Guzmán, Philipp Koehn, Naman Goyal and Peng‐Jen Chen. Their work appears in journals such as Journal of Machine Learning Research, Proceedings of the VLDB Endowment and Minerva Access (University of Melbourne).
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.