Sara Hooker
Impact in
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
- Artificial Intelligence top 5%
- Explainable Artificial Intelligence (XAI)
- Adversarial Robustness in Machine Learning
- Topic Modeling
- Machine Learning and Data Classification
- Natural Language Processing Techniques
Papers in
-
- Natural Language Processing Techniques 5
- Adversarial Robustness in Machine Learning 4
- Topic Modeling 4
- Explainable Artificial Intelligence (XAI) 3
- Machine Learning and Data Classification 2
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- Advanced Neural Network Applications 2
- Co-authors
- Pieter-Jan Kindermans (1 shared paper)Maximilian Alber (1 shared paper)Sven Dähne (1 shared paper)Dumitru Erhan (1 shared paper)Kristof T. Schütt (1 shared paper)Been Kim (1 shared paper)Julius Adebayo (1 shared paper)Daniel D’souza (2 shared papers)
- Journals
- Nature Machine Intelligence (2 papers)Patterns (1 paper)Nature (1 paper)Lecture notes in computer science (1 paper)2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (1 paper)
- Partner nations
- United StatesCanadaUnited Kingdom
In The Last Decade
Sara Hooker
16 papers receiving 495 citations
Peers
Comparison fields: 5 of 104
- Health Informatics 56
- Artificial Intelligence 348
- Safety Research 62
- Computer Vision and Pattern Recognition 74
- Biophysics 17
Countries citing papers authored by Sara Hooker
This map shows the geographic impact of Sara Hooker'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 Sara Hooker with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sara Hooker more than expected).
Fields of papers citing papers by Sara Hooker
This network shows the impact of papers produced by Sara Hooker. 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 Sara Hooker. The network helps show where Sara Hooker may publish in the future.
Co-authors
The 25 scholars most cited alongside Sara Hooker, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 265 | |
| 2 | 2021 | 109 | |
| 3 | 2022 | 33 | |
| 4 | 2024 | 32 | |
| 5 | 2024 | 25 | |
| 6 | 2023 | 12 | |
| 7 | 2024 | 11 | |
| 8 | 2023 | 7 | |
| 9 | 2024 | 7 | |
| 10 | Selective Brain Damage: Measuring the Disparate Impact of Model Pruning | 2019 | 7 |
| 11 | 2024 | 3 | |
| 12 | 2024 | 3 | |
| 13 | 2022 | 2 | |
| 14 | 2025 | 2 | |
| 15 | 2024 | 1 | |
| 16 | 2024 | 1 | |
| 17 | 2025 | 0 | |
| 18 | 2023 | 0 | |
| 19 | 2024 | 0 | |
| 20 | 2023 | 0 |
About Sara Hooker
Sara Hooker is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Health Informatics, Safety Research and Molecular Biology, having authored 21 papers that have together received 520 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (5 papers), Adversarial Robustness in Machine Learning (4 papers), Topic Modeling (4 papers), Explainable Artificial Intelligence (XAI) (3 papers), Advanced Neural Network Applications (2 papers), Machine Learning and Data Classification (2 papers), Artificial Intelligence in Healthcare and Education (2 papers) and Ethics and Social Impacts of AI (2 papers). The work is most often cited by research in Health Informatics (56 citations), Artificial Intelligence (348 citations), Safety Research (62 citations), Computer Vision and Pattern Recognition (74 citations) and Biophysics (17 citations). Sara Hooker has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Pieter-Jan Kindermans, Maximilian Alber, Sven Dähne, Dumitru Erhan, Kristof T. Schütt, Been Kim, Julius Adebayo, Daniel D’souza, Chirag Agarwal and Julia Kreutzer. Their work appears in journals such as Nature Machine Intelligence, Patterns, Nature, Lecture notes in computer science and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
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.