Mikaela Keller
- Epidemiology top 10%
- Public Health, Environmental and Occupational Health top 10%
- Modeling and Simulation top 2%
- Infectious Diseases
- Sociology and Political Science
- Co-authors
- John S. BrownsteinAbla MawudekuEmily H. ChanClark C. FreifeldSamy BengioDavid L. BuckeridgeGünther EysenbachHerman Tolentino
- Topics
- Data-Driven Disease Surveillance (7 papers)Topic Modeling (6 papers)Text and Document Classification Technologies (4 papers)
- Journals
- New England Journal of MedicineProceedings of the National Academy of SciencesEmerging infectious diseases
- Partner nations
- United StatesCanadaFrance
In The Last Decade
Mikaela Keller
15 papers receiving 482 citations
Peers
Comparison fields: 5 of 97
- Epidemiology 265
- Public Health, Environmental and Occupational Health 177
- Modeling and Simulation 117
- Infectious Diseases 110
- Sociology and Political Science 68
Countries citing papers authored by Mikaela Keller
This map shows the geographic impact of Mikaela Keller'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 Mikaela Keller with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mikaela Keller more than expected).
Fields of papers citing papers by Mikaela Keller
This network shows the impact of papers produced by Mikaela Keller. 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 Mikaela Keller. The network helps show where Mikaela Keller may publish in the future.
Co-authorship network of co-authors of Mikaela Keller
This figure shows the co-authorship network connecting the top 25 collaborators of Mikaela Keller. A scholar is included among the top collaborators of Mikaela Keller 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 Mikaela Keller. Mikaela Keller is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 2 | |
| 3 | 5 | |
| 4 | 22 | |
| 5 | 17 | |
| 6 | 4 | |
| 7 | 166 | |
| 8 | 76 | |
| 9 | 141 | |
| 10 | 14 | |
| 11 | A Multitask Learning Approach to Document Representation using Unlabeled Data | 3 |
| 12 | 9 | |
| 13 | Benchmarking Non-Parametric Statistical Tests | 7 |
| 14 | Theme Topic Mixture Model: A Graphical Model for Document Representation | 9 |
| 15 | The Expected Performance Curve | 48 |
About Mikaela Keller
Mikaela Keller is a scholar working on Modeling and Simulation, Artificial Intelligence and Epidemiology, having authored 15 papers that have together received 527 indexed citations. Recurring topics across this work include Data-Driven Disease Surveillance (7 papers), Topic Modeling (6 papers) and Text and Document Classification Technologies (4 papers). The work is most often cited by research in Modeling and Simulation (117 citations), Epidemiology (265 citations) and Health (54 citations). Mikaela Keller has collaborated with scholars based in United States, Canada and France. Frequent co-authors include John S. Brownstein, Abla Mawudeku, Emily H. Chan, Clark C. Freifeld, Samy Bengio, Clark C. Freifeld, David L. Buckeridge, Günther Eysenbach, Herman Tolentino and Kenneth D. Mandl. Their work appears in journals such as New England Journal of Medicine, Proceedings of the National Academy of Sciences and Emerging infectious diseases.
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.