Regina Barzilay
- Artificial Intelligence top 0.05%
- Computational Theory and Mathematics top 0.05%
- Molecular Biology top 2%
- Materials Chemistry top 2%
- Computer Vision and Pattern Recognition top 1%
- Co-authors
- Tommi JaakkolaKathleen McKeownMirella LapataMichael ElhadadKlavs F. JensenConnor W. ColeyWengong JinLillian Lee
- Topics
- Topic Modeling (105 papers)Natural Language Processing Techniques (89 papers)Computational Drug Discovery Methods (28 papers)
- Partner nations
- United StatesCanadaUnited Kingdom
In The Last Decade
Regina Barzilay
198 papers receiving 13.7k citations
Hit Papers
Peers
Comparison fields: 5 of 218
- Artificial Intelligence 8.9k
- Computational Theory and Mathematics 3.0k
- Molecular Biology 2.8k
- Materials Chemistry 2.5k
- Computer Vision and Pattern Recognition 1.2k
Countries citing papers authored by Regina Barzilay
This map shows the geographic impact of Regina Barzilay'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 Regina Barzilay with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Regina Barzilay more than expected).
Fields of papers citing papers by Regina Barzilay
This network shows the impact of papers produced by Regina Barzilay. 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 Regina Barzilay. The network helps show where Regina Barzilay may publish in the future.
Co-authorship network of co-authors of Regina Barzilay
This figure shows the co-authorship network connecting the top 25 collaborators of Regina Barzilay. A scholar is included among the top collaborators of Regina Barzilay 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 Regina Barzilay. Regina Barzilay is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | 11 | |
| 3 | 15 | |
| 4 | Deep learning-guided discovery of an antibiotic targeting Acinetobacter baumanniibreakdown → | 183 |
| 5 | Sybil: A Validated Deep Learning Model to Predict Future Lung Cancer Risk From a Single Low-Dose Chest Computed Tomographybreakdown → | 114 |
| 6 | 1 | |
| 7 | 57 | |
| 8 | 114 | |
| 9 | 135 | |
| 10 | 89 | |
| 11 | 8 | |
| 12 | 48 | |
| 13 | 25 | |
| 14 | A graph-convolutional neural network model for the prediction of chemical reactivitybreakdown → | 460 |
| 15 | 208 | |
| 16 | Using Universal Linguistic Knowledge to Guide Grammar Induction | 83 |
| 17 | Climbing the Tower of Babel: Unsupervised Multilingual Learning | 8 |
| 18 | A Statistical Model for Lost Language Decipherment | 31 |
| 19 | 114 | |
| 20 | Incremental Text Structuring with Online Hierarchical Ranking | 11 |
About Regina Barzilay
Regina Barzilay is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Computer Vision and Pattern Recognition, having authored 199 papers that have together received 14.8k indexed citations. Recurring topics across this work include Topic Modeling (105 papers), Natural Language Processing Techniques (89 papers) and Computational Drug Discovery Methods (28 papers). The work is most often cited by research in Health Informatics (405 citations), Artificial Intelligence (8.9k citations) and Computational Theory and Mathematics (3.0k citations). Regina Barzilay has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Tommi Jaakkola, Kathleen McKeown, Mirella Lapata, Michael Elhadad, Klavs F. Jensen, Connor W. Coley, Wengong Jin, Lillian Lee, William H. Green and Benjamin Snyder. Their work appears in journals such as Science, Cell and Proceedings of the National Academy of Sciences.
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.