Dafna Shahaf
-
- Mobile Crowdsensing and Crowdsourcing 5
- Artificial Intelligence top 2%
- Topic Modeling 13
- Natural Language Processing Techniques 10
- Advanced Text Analysis Techniques 8
- Logic, Reasoning, and Knowledge 5
-
- Data Visualization and Analytics 7
- Multimodal Machine Learning Applications 6
- Information Systems top 5%
- Web Data Mining and Analysis 7
- Co-authors
- Carlos GuestrinEric HorvitzAviv TamarMichael SchapiraAsaf ValadarskyTom HopeJoel ChanAniket Kittur
- Cited by
- Computer Science ApplicationsArtificial IntelligenceComputer Vision and Pattern Recognition
- Journals
- Proceedings of the National Academy of Sciences (2 papers)Communications of the ACM (2 papers)Transactions of the Association for Computational Linguistics (1 paper)
- Partner nations
- United StatesIsraelUnited Kingdom
In The Last Decade
Dafna Shahaf
46 papers receiving 983 citations
Peers
Comparison fields: 5 of 89
- Computer Science Applications 96
- Artificial Intelligence 556
- Computer Vision and Pattern Recognition 211
- Information Systems 231
- Statistical and Nonlinear Physics 125
Countries citing papers authored by Dafna Shahaf
This map shows the geographic impact of Dafna Shahaf'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 Dafna Shahaf with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dafna Shahaf more than expected).
Fields of papers citing papers by Dafna Shahaf
This network shows the impact of papers produced by Dafna Shahaf. 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 Dafna Shahaf. The network helps show where Dafna Shahaf may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Dafna Shahaf, 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 | 2 | |
| 2 | 2024 | 2 | |
| 3 | 2023 | 4 | |
| 4 | 2023 | 2 | |
| 5 | 2022 | 5 | |
| 6 | 2022 | 5 | |
| 7 | 2022 | 2 | |
| 8 | 2022 | 7 | |
| 9 | 2019 | 55 | |
| 10 | 2017 | 143 | |
| 11 | 2017 | 13 | |
| 12 | 2012 | 46 | |
| 13 | 2011 | 3 | |
| 14 | 2010 | 123 | |
| 15 | Learning Thin Junction Trees via Graph Cuts | 2009 | 18 |
| 16 | Investigations of continual computation | 2009 | 3 |
| 17 | Towards a theory of AI completeness | 2007 | 26 |
| 18 | Logical circuit filtering | 2007 | 5 |
| 19 | Learning partially observable action schemas | 2006 | 21 |
| 20 | Learning partially observable action models: efficient algorithms | 2006 | 9 |
About Dafna Shahaf
Dafna Shahaf is a scholar working on Computer Science Applications, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 46 papers that have together received 1.0k indexed citations. Recurring topics across this work include Topic Modeling (13 papers), Natural Language Processing Techniques (10 papers), Advanced Text Analysis Techniques (8 papers), Data Visualization and Analytics (7 papers), Web Data Mining and Analysis (7 papers), Multimodal Machine Learning Applications (6 papers), Logic, Reasoning, and Knowledge (5 papers) and Mobile Crowdsensing and Crowdsourcing (5 papers). The work is most often cited by research in Computer Science Applications (96 citations), Artificial Intelligence (556 citations) and Computer Vision and Pattern Recognition (211 citations). Dafna Shahaf has collaborated with scholars based in United States, Israel and United Kingdom. Frequent co-authors include Carlos Guestrin, Eric Horvitz, Aviv Tamar, Michael Schapira, Asaf Valadarsky, Tom Hope, Joel Chan, Aniket Kittur, Eyal Amir and Jure Leskovec. Their work appears in journals such as Proceedings of the National Academy of Sciences, Communications of the ACM, Transactions of the Association for Computational Linguistics, Proceedings of the ACM on Human-Computer Interaction and ACM Transactions on Knowledge Discovery from Data.
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.