John DeNero
- Artificial Intelligence top 1%
- Topic Modeling 34
- Natural Language Processing Techniques 32
- Speech and dialogue systems 7
- Algorithms and Data Compression 4
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- Teaching and Learning Programming 7
- Software top 10%
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- Multimodal Machine Learning Applications 6
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- Biomedical Text Mining and Ontologies 4
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- Software Engineering Research 3
John DeNero
49 papers receiving 944 citations
Peers
Comparison fields: 5 of 80
- Artificial Intelligence 942
- Computer Science Applications 73
- Software 25
- Computer Vision and Pattern Recognition 115
- Health Informatics 6
Countries citing papers authored by John DeNero
This map shows the geographic impact of John DeNero'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 John DeNero with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John DeNero more than expected).
Fields of papers citing papers by John DeNero
This network shows the impact of papers produced by John DeNero. 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 John DeNero. The network helps show where John DeNero may publish in the future.
Co-authorship network
The 25 scholars most cited alongside John DeNero, 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 | 2025 | 1 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 9 | |
| 4 | 2025 | 1 | |
| 5 | 2021 | 5 | |
| 6 | Investigating the Behavior of Malicious Actors Through the Game of Mafia. | 2020 | 1 |
| 7 | 2019 | 4 | |
| 8 | Supervised Learning of Complete Morphological Paradigms | 2013 | 78 |
| 9 | 2013 | 6 | |
| 10 | A Feature-Rich Constituent Context Model for Grammar Induction | 2012 | 7 |
| 11 | A Class-Based Agreement Model for Generating Accurately Inflected Translations | 2012 | 37 |
| 12 | Unsupervised Translation Sense Clustering | 2012 | 12 |
| 13 | Model-Based Aligner Combination Using Dual Decomposition | 2011 | 21 |
| 14 | Inducing Sentence Structure from Parallel Corpora for Reordering | 2011 | 37 |
| 15 | Discriminative Modeling of Extraction Sets for Machine Translation | 2010 | 17 |
| 16 | Painless Unsupervised Learning with Features | 2010 | 152 |
| 17 | Model Combination for Machine Translation | 2010 | 21 |
| 18 | Approximate Factoring for A* Search | 2007 | 6 |
| 19 | Tailoring Word Alignments to Syntactic Machine Translation | 2007 | 75 |
| 20 | 2007 | 1 |
About John DeNero
John DeNero is a scholar working on Computer Science Applications, Artificial Intelligence, Software, Computer Vision and Pattern Recognition and Information Systems, having authored 52 papers that have together received 1.1k indexed citations. Recurring topics across this work include Topic Modeling (34 papers), Natural Language Processing Techniques (32 papers), Speech and dialogue systems (7 papers), Teaching and Learning Programming (7 papers), Multimodal Machine Learning Applications (6 papers), Biomedical Text Mining and Ontologies (4 papers), Algorithms and Data Compression (4 papers) and Software Engineering Research (3 papers). The work is most often cited by research in Artificial Intelligence (942 citations), Computer Science Applications (73 citations), Software (25 citations), Computer Vision and Pattern Recognition (115 citations) and Health Informatics (6 citations). John DeNero has collaborated with scholars based in United States, Canada and Singapore. Frequent co-authors include Dan Klein, Alexandre Bouchard‐Côté, Greg Durrett, Taylor Berg-Kirkpatrick, Spence Green, Aria Haghighi, Jakob Uszkoreit, John Blitzer, Robert C. Moore and James Zhang. Their work appears in journals such as Journal of Biomedical Informatics, Cognitive Science, JAMIA Open, JMIR Research Protocols and North American Chapter of the Association for Computational Linguistics.
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.