Uriel Singer
Impact in
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- Computer Graphics and Visualization Techniques
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- Generative Adversarial Networks and Image Synthesis
- Advanced Image and Video Retrieval Techniques
Papers in
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- Advanced Graph Neural Networks 2
- Advanced Text Analysis Techniques 1
- Co-authors
- Kira Radinsky (7 shared papers)Adam Polyak (2 shared papers)Haggai Roitman (1 shared paper)Eliyahu Kiperwasser (1 shared paper)Devi Parikh (1 shared paper)Eric Horvitz (1 shared paper)Shelly Sheynin (1 shared paper)Oron Ashual (1 shared paper)
- Journals
- Bioinformatics (1 paper)Proceedings of the 31st ACM International Conference on Information & Knowledge Management (1 paper)arXiv (Cornell University) (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)PubMed (1 paper)
- Partner nations
- IsraelUnited States
In The Last Decade
Uriel Singer
10 papers receiving 57 citations
Peers
Comparison fields: 5 of 26
- Computer Graphics and Computer-Aided Design 6
- Computer Vision and Pattern Recognition 17
- Artificial Intelligence 23
- Computational Theory and Mathematics 10
- Information Systems 14
Countries citing papers authored by Uriel Singer
This map shows the geographic impact of Uriel Singer'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 Uriel Singer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Uriel Singer more than expected).
Fields of papers citing papers by Uriel Singer
This network shows the impact of papers produced by Uriel Singer. 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 Uriel Singer. The network helps show where Uriel Singer may publish in the future.
Co-authors
The 13 scholars most cited alongside Uriel Singer, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 18 | |
| 2 | 2022 | 12 | |
| 3 | 2020 | 6 | |
| 4 | 2023 | 6 | |
| 5 | 2022 | 6 | |
| 6 | 2022 | 4 | |
| 7 | 2023 | 2 | |
| 8 | 2023 | 2 | |
| 9 | 2022 | 2 | |
| 10 | 2024 | 1 |
About Uriel Singer
Uriel Singer is a scholar working on Artificial Intelligence, Molecular Biology, Computational Theory and Mathematics, Transportation and Organic Chemistry, having authored 10 papers that have together received 59 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (2 papers), Human Mobility and Location-Based Analysis (2 papers), Advanced Graph Neural Networks (2 papers), Complex Network Analysis Techniques (1 paper), Advanced Text Analysis Techniques (1 paper), Time Series Analysis and Forecasting (1 paper), Multimodal Machine Learning Applications (1 paper) and Ethics and Social Impacts of AI (1 paper). The work is most often cited by research in Computer Graphics and Computer-Aided Design (6 citations), Computer Vision and Pattern Recognition (17 citations), Artificial Intelligence (23 citations), Computational Theory and Mathematics (10 citations) and Information Systems (14 citations). Uriel Singer has collaborated with scholars based in Israel and United States. Frequent co-authors include Kira Radinsky, Adam Polyak, Haggai Roitman, Eliyahu Kiperwasser, Devi Parikh, Eric Horvitz, Shelly Sheynin, Oron Ashual, Yaniv Taigman and Ido Guy. Their work appears in journals such as Bioinformatics, Proceedings of the 31st ACM International Conference on Information & Knowledge Management, arXiv (Cornell University), Proceedings of the AAAI Conference on Artificial Intelligence and PubMed.
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.