Nouha Dziri
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 10%
- Experimental and Cognitive Psychology
- Social Psychology
- Information Systems
- Co-authors
- Osmar R. Zaı̈aneChenyang HuangAmine TrabelsiSiva ReddyMo YuEhsan KamallooAvishek Joey BoseAndrea Madotto
- Topics
- Topic Modeling (9 papers)Natural Language Processing Techniques (7 papers)Multimodal Machine Learning Applications (4 papers)
- Journals
- Transactions of the Association for Computational LinguisticsarXiv (Cornell University)Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
- Partner nations
- United StatesCanadaUnited Kingdom
In The Last Decade
Nouha Dziri
15 papers receiving 296 citations
Peers
Comparison fields: 5 of 46
- Artificial Intelligence 252
- Computer Vision and Pattern Recognition 64
- Experimental and Cognitive Psychology 22
- Social Psychology 19
- Information Systems 17
Countries citing papers authored by Nouha Dziri
This map shows the geographic impact of Nouha Dziri'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 Nouha Dziri with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nouha Dziri more than expected).
Fields of papers citing papers by Nouha Dziri
This network shows the impact of papers produced by Nouha Dziri. 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 Nouha Dziri. The network helps show where Nouha Dziri may publish in the future.
Co-authorship network of co-authors of Nouha Dziri
This figure shows the co-authorship network connecting the top 25 collaborators of Nouha Dziri. A scholar is included among the top collaborators of Nouha Dziri 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 Nouha Dziri. Nouha Dziri 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 | 1 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 6 | |
| 7 | 0 | |
| 8 | 40 | |
| 9 | 4 | |
| 10 | 2 | |
| 11 | 3 | |
| 12 | 16 | |
| 13 | 75 | |
| 14 | 27 | |
| 15 | 43 | |
| 16 | 5 | |
| 17 | 84 |
About Nouha Dziri
Nouha Dziri is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Safety Research, having authored 17 papers that have together received 310 indexed citations. Recurring topics across this work include Topic Modeling (9 papers), Natural Language Processing Techniques (7 papers) and Multimodal Machine Learning Applications (4 papers). The work is most often cited by research in Health Informatics (11 citations), Artificial Intelligence (252 citations) and Computer Vision and Pattern Recognition (64 citations). Nouha Dziri has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Osmar R. Zaı̈ane, Chenyang Huang, Amine Trabelsi, Siva Reddy, Mo Yu, Ehsan Kamalloo, Avishek Joey Bose, Andrea Madotto, Davood Rafiei and Charles L. A. Clarke. Their work appears in journals such as Transactions of the Association for Computational Linguistics, arXiv (Cornell University) and Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing.
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.