Naomi Saphra
- Artificial Intelligence
- Computer Vision and Pattern Recognition
- Information Systems
- Sociology and Political Science
- Computer Science Applications
- Co-authors
- Mohammad TahaeiKami VanieaAdam LopezDavid WeißJuho KannalaStavros TsogkasIasonas KokkinosKaren Simonyan
- Topics
- Topic Modeling (5 papers)Natural Language Processing Techniques (4 papers)Software Engineering Research (2 papers)
- Cited by
- Computer Vision and Pattern RecognitionArtificial IntelligenceComputer Science Applications
- Journals
- Nature Machine IntelligenceEdinburgh Research Explorer (University of Edinburgh)Edinburgh Research Explorer
- Partner nations
- United KingdomUnited StatesSwitzerland
In The Last Decade
Naomi Saphra
9 papers receiving 151 citations
Peers
Comparison fields: 5 of 58
- Artificial Intelligence 74
- Computer Vision and Pattern Recognition 48
- Information Systems 39
- Sociology and Political Science 33
- Computer Science Applications 12
Countries citing papers authored by Naomi Saphra
This map shows the geographic impact of Naomi Saphra'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 Naomi Saphra with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Naomi Saphra more than expected).
Fields of papers citing papers by Naomi Saphra
This network shows the impact of papers produced by Naomi Saphra. 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 Naomi Saphra. The network helps show where Naomi Saphra may publish in the future.
Co-authorship network of co-authors of Naomi Saphra
This figure shows the co-authorship network connecting the top 25 collaborators of Naomi Saphra. A scholar is included among the top collaborators of Naomi Saphra 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 Naomi Saphra. Naomi Saphra 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 | 1 | |
| 3 | 29 | |
| 4 | 56 | |
| 5 | 5 | |
| 6 | 3 | |
| 7 | 6 | |
| 8 | 50 | |
| 9 | 7 |
About Naomi Saphra
Naomi Saphra is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems, having authored 9 papers that have together received 158 indexed citations. Recurring topics across this work include Topic Modeling (5 papers), Natural Language Processing Techniques (4 papers) and Software Engineering Research (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (48 citations), Artificial Intelligence (74 citations) and Computer Science Applications (12 citations). Naomi Saphra has collaborated with scholars based in United Kingdom, United States and Switzerland. Frequent co-authors include Mohammad Tahaei, Kami Vaniea, Adam Lopez, David Weiß, Juho Kannala, Stavros Tsogkas, Iasonas Kokkinos, Karen Simonyan, Andrea Vedaldi and Ben Taskar. Their work appears in journals such as Nature Machine Intelligence, Edinburgh Research Explorer (University of Edinburgh) and Edinburgh Research Explorer.
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.