Drew Dimmery
Impact in
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- Consumer Market Behavior and Pricing
Papers in
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- Advanced Causal Inference Techniques 3
- Statistical Methods in Clinical Trials 3
- Statistical Methods and Inference 2
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- Machine Learning in Healthcare 1
- Data Stream Mining Techniques 1
- Co-authors
- Yan Leng (2 shared papers)Andrew Peterson (1 shared paper)Weiwei Li (1 shared paper)Adam Obeng (1 shared paper)Daniel Jiang (1 shared paper)Han Wu (1 shared paper)Eytan Bakshy (1 shared paper)Mia R. Garrard (1 shared paper)
- Journals
- RSF The Russell Sage Foundation Journal of the Social Sciences (1 paper)Information Systems Research (1 paper)International Conference on Artificial Intelligence and Statistics (1 paper)SSRN Electronic Journal (1 paper)Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (1 paper)
- Partner nations
- United StatesAustriaIsrael
In The Last Decade
Drew Dimmery
4 papers receiving 7 citations
Peers
Comparison fields: 5 of 14
- Marketing 2
- Information Systems and Management 1
- Statistics and Probability 1
- General Agricultural and Biological Sciences 1
- Soil Science 1
Countries citing papers authored by Drew Dimmery
This map shows the geographic impact of Drew Dimmery'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 Drew Dimmery with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Drew Dimmery more than expected).
Fields of papers citing papers by Drew Dimmery
This network shows the impact of papers produced by Drew Dimmery. 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 Drew Dimmery. The network helps show where Drew Dimmery may publish in the future.
Co-authors
The 9 scholars most cited alongside Drew Dimmery, 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 | 3 | |
| 2 | 2016 | 3 | |
| 3 | Balanced Off-Policy Evaluation in General Action Spaces | 2020 | 1 |
| 4 | 2021 | 1 | |
| 5 | 2022 | 0 |
About Drew Dimmery
Drew Dimmery is a scholar working on Statistics and Probability, Artificial Intelligence, Communication, Sociology and Political Science and General Social Sciences, having authored 5 papers that have together received 8 indexed citations. Recurring topics across this work include Advanced Causal Inference Techniques (3 papers), Statistical Methods in Clinical Trials (3 papers), Statistical Methods and Inference (2 papers), Computational and Text Analysis Methods (1 paper), Media Influence and Politics (1 paper), Social Media and Politics (1 paper), Machine Learning in Healthcare (1 paper) and Data Stream Mining Techniques (1 paper). The work is most often cited by research in Marketing (2 citations), Information Systems and Management (1 citation), Statistics and Probability (1 citation), General Agricultural and Biological Sciences (1 citation) and Soil Science (1 citation). Drew Dimmery has collaborated with scholars based in United States, Austria and Israel. Frequent co-authors include Yan Leng, Andrew Peterson, Weiwei Li, Adam Obeng, Daniel Jiang, Han Wu, Eytan Bakshy, Mia R. Garrard and Sarah Tan. Their work appears in journals such as RSF The Russell Sage Foundation Journal of the Social Sciences, Information Systems Research, International Conference on Artificial Intelligence and Statistics, SSRN Electronic Journal and Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining.
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.