Shira Mitchell
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
- Safety Research top 2%
- Ethics and Social Impacts of AI
Papers in
-
- Adversarial Robustness in Machine Learning 1
- Natural Language Processing Techniques 1
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- Census and Population Estimation 1
- Statistical Methods and Bayesian Inference 1
- Co-authors
- Kristian Lum (2 shared papers)Alexander D’Amour (1 shared paper)Solon Barocas (1 shared paper)Eric Potash (1 shared paper)Štefan Beňuš (1 shared paper)Ilia Vovsha (1 shared paper)Agustı́n Gravano (1 shared paper)Julia Hirschberg (1 shared paper)
- Journals
- Biometrics (1 paper)The Lancet Global Health (1 paper)Tropical Medicine & International Health (1 paper)American Journal of Tropical Medicine and Hygiene (1 paper)Annual Review of Statistics and Its Application (1 paper)
- Partner nations
- United StatesMalawiUnited Kingdom
In The Last Decade
Shira Mitchell
8 papers receiving 379 citations
Shira Mitchell's Hit Papers
Peers
Comparison fields: 5 of 92
- Health Informatics 35
- Safety Research 176
- Artificial Intelligence 135
- Computer Science Applications 18
- Statistics and Probability 23
Countries citing papers authored by Shira Mitchell
This map shows the geographic impact of Shira Mitchell'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 Shira Mitchell with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shira Mitchell more than expected).
Fields of papers citing papers by Shira Mitchell
This network shows the impact of papers produced by Shira Mitchell. 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 Shira Mitchell. The network helps show where Shira Mitchell may publish in the future.
Co-authors
The 25 scholars most cited alongside Shira Mitchell, 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 | Algorithmic Fairness: Choices, Assumptions, and Definitions Hit paper breakdown → | 2020 | 300 |
| 2 | 2018 | 30 | |
| 3 | 2007 | 27 | |
| 4 | 2012 | 13 | |
| 5 | 2012 | 10 | |
| 6 | 2024 | 6 | |
| 7 | 2013 | 4 | |
| 8 | 2012 | 1 |
About Shira Mitchell
Shira Mitchell is a scholar working on Artificial Intelligence, Statistics and Probability, Parasitology, General Health Professions and Epidemiology, having authored 8 papers that have together received 391 indexed citations. Recurring topics across this work include Parasites and Host Interactions (2 papers), Health and Conflict Studies (1 paper), Census and Population Estimation (1 paper), Data-Driven Disease Surveillance (1 paper), Adversarial Robustness in Machine Learning (1 paper), Natural Language Processing Techniques (1 paper), Language, Discourse, Communication Strategies (1 paper) and Statistical Methods and Bayesian Inference (1 paper). The work is most often cited by research in Health Informatics (35 citations), Safety Research (176 citations), Artificial Intelligence (135 citations), Computer Science Applications (18 citations) and Statistics and Probability (23 citations). Shira Mitchell has collaborated with scholars based in United States, Malawi and United Kingdom. Frequent co-authors include Kristian Lum, Alexander D’Amour, Solon Barocas, Eric Potash, Štefan Beňuš, Ilia Vovsha, Agustı́n Gravano, Julia Hirschberg, Bethany Hedt‐Gauthier and Matthew W. Harris. Their work appears in journals such as Biometrics, The Lancet Global Health, Tropical Medicine & International Health, American Journal of Tropical Medicine and Hygiene and Annual Review of Statistics and Its Application.
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.