Michael Katell
Impact in
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
- Safety Research top 2%
- Ethics and Social Impacts of AI
Papers in
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- Ethics and Social Impacts of AI 15
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- Privacy-Preserving Technologies in Data 4
- Law, AI, and Intellectual Property 2
- Co-authors
- P. M. Krafft (8 shared papers)Meg Young (7 shared papers)Dharma Dailey (3 shared papers)Karen Huang (1 shared paper)Mhairi Aitken (11 shared papers)David Leslie (11 shared papers)Christopher Burr (4 shared papers)Josh Cowls (1 shared paper)
- Journals
- Big Data & Society (1 paper)Law Innovation and Technology (1 paper)interactions (1 paper)Nature Reviews Genetics (1 paper)Proceedings of the Association for Information Science and Technology (1 paper)
- Partner nations
- United StatesUnited KingdomIreland
In The Last Decade
Michael Katell
25 papers receiving 424 citations
Peers
Comparison fields: 5 of 77
- Health Informatics 53
- Safety Research 258
- Computer Science Applications 54
- Human-Computer Interaction 50
- Artificial Intelligence 134
Countries citing papers authored by Michael Katell
This map shows the geographic impact of Michael Katell'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 Michael Katell with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Katell more than expected).
Fields of papers citing papers by Michael Katell
This network shows the impact of papers produced by Michael Katell. 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 Michael Katell. The network helps show where Michael Katell may publish in the future.
Co-authors
The 25 scholars most cited alongside Michael Katell, 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 27 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 101 | |
| 2 | 2020 | 79 | |
| 3 | 2021 | 60 | |
| 4 | 2021 | 47 | |
| 5 | 2022 | 38 | |
| 6 | 2019 | 33 | |
| 7 | 2024 | 11 | |
| 8 | 2021 | 10 | |
| 9 | 2022 | 10 | |
| 10 | 2019 | 8 | |
| 11 | 2021 | 8 | |
| 12 | 2024 | 7 | |
| 13 | 2020 | 7 | |
| 14 | 2019 | 5 | |
| 15 | 2022 | 5 | |
| 16 | 2024 | 5 | |
| 17 | 2016 | 3 | |
| 18 | 2018 | 2 | |
| 19 | 2025 | 1 | |
| 20 | 2015 | 1 |
About Michael Katell
Michael Katell is a scholar working on Safety Research, Artificial Intelligence, Sociology and Political Science, Information Systems and Law, having authored 27 papers that have together received 446 indexed citations. Recurring topics across this work include Ethics and Social Impacts of AI (15 papers), Privacy, Security, and Data Protection (6 papers), Privacy-Preserving Technologies in Data (4 papers), COVID-19 Digital Contact Tracing (3 papers), Mobile Crowdsensing and Crowdsourcing (3 papers), Data Quality and Management (2 papers), Law, AI, and Intellectual Property (2 papers) and Legal and Policy Issues (2 papers). The work is most often cited by research in Health Informatics (53 citations), Safety Research (258 citations), Computer Science Applications (54 citations), Human-Computer Interaction (50 citations) and Artificial Intelligence (134 citations). Michael Katell has collaborated with scholars based in United States, United Kingdom and Ireland. Frequent co-authors include P. M. Krafft, Meg Young, Dharma Dailey, Karen Huang, Mhairi Aitken, David Leslie, Christopher Burr, Josh Cowls, Jennifer E. Lee and Jennifer Lee. Their work appears in journals such as Big Data & Society, Law Innovation and Technology, interactions, Nature Reviews Genetics and Proceedings of the Association for Information Science and Technology.
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.