Bob Carpenter
- Statistics and Probability top 0.5%
- General Decision Sciences top 5%
- Ecological Modeling top 5%
- Artificial Intelligence top 1%
- Natural Language Processing Techniques 8
- Logic, Reasoning, and Knowledge 6
- Topic Modeling 4
- Bayesian Modeling and Causal Inference 2
- Speech and dialogue systems 2
- Logic, programming, and type systems 2
- Modeling and Simulation top 2%
- COVID-19 epidemiological studies 2
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- SARS-CoV-2 and COVID-19 Research 2
- Co-authors
- Marcus A. BrubakerPeter LiJiqiang GuoDaniel C. LeeMatthew D. HoffmanMichael BetancourtAllen RiddellBen Goodrich
- Journals
- Transactions of the Association for Computational Linguistics (2 papers)Scientific Reports (1 paper)The Journal of Chemical Physics (1 paper)
- Partner nations
- United StatesUnited KingdomItaly
In The Last Decade
Bob Carpenter
26 papers receiving 5.4k citations
Hit Papers
Peers
Comparison fields: 5 of 223
- Statistics and Probability 694
- General Decision Sciences 117
- Ecological Modeling 188
- Artificial Intelligence 1.2k
- Modeling and Simulation 172
Countries citing papers authored by Bob Carpenter
This map shows the geographic impact of Bob Carpenter'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 Bob Carpenter with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bob Carpenter more than expected).
Fields of papers citing papers by Bob Carpenter
This network shows the impact of papers produced by Bob Carpenter. 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 Bob Carpenter. The network helps show where Bob Carpenter may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Bob Carpenter, 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 | 0 | |
| 2 | 2024 | 0 | |
| 3 | 2023 | 1 | |
| 4 | 2023 | 3 | |
| 5 | 2023 | 2 | |
| 6 | 2022 | 14 | |
| 7 | 2021 | 32 | |
| 8 | 2020 | 65 | |
| 9 | 2018 | 1 | |
| 10 | Stan: A Probabilistic Programming Languagebreakdown → | 2017 | 496 |
| 11 | Stan: A Probabilistic Programming Languagebreakdown → | 2017 | 4257 |
| 12 | A Hierarchical Bayesian Model of Crowdsourced Relevance Coding. | 2011 | 10 |
| 13 | Software Engineering, Testing, and Quality Assurance for Natural Language Processing | 2008 | 2 |
| 14 | Logic of Typed Feature Structures, The (Cambridge Tracts in Theoretical Computer Science) | 2005 | 23 |
| 15 | Phrasal Queries with LingPipe and Lucene: Ad Hoc Genomics Text Retrieval. | 2004 | 28 |
| 16 | 2004 | 10 | |
| 17 | 1996 | 84 | |
| 18 | The logic of typed feature structures | 1992 | 348 |
| 19 | 1991 | 4 | |
| 20 | 1990 | 3 |
About Bob Carpenter
Bob Carpenter is a scholar working on Structural Biology, Artificial Intelligence and Modeling and Simulation, having authored 28 papers that have together received 5.7k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (8 papers), Logic, Reasoning, and Knowledge (6 papers), Topic Modeling (4 papers), SARS-CoV-2 and COVID-19 Research (2 papers), COVID-19 epidemiological studies (2 papers), Bayesian Modeling and Causal Inference (2 papers), Speech and dialogue systems (2 papers) and Logic, programming, and type systems (2 papers). The work is most often cited by research in Statistics and Probability (694 citations), General Decision Sciences (117 citations) and Ecological Modeling (188 citations). Bob Carpenter has collaborated with scholars based in United States, United Kingdom and Italy. Frequent co-authors include Marcus A. Brubaker, Peter Li, Jiqiang Guo, Daniel C. Lee, Matthew D. Hoffman, Michael Betancourt, Allen Riddell, Ben Goodrich, Andrew Gelman and Andrew Gelman. Their work appears in journals such as Transactions of the Association for Computational Linguistics, Scientific Reports, The Journal of Chemical Physics, Journal of Statistical Software and Journal of the Royal Statistical Society Series C (Applied Statistics).
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.